n?u=RePEc:bdi:wptemi:td_1064_16&r=mac

repec.nep.mac

n?u=RePEc:bdi:wptemi:td_1064_16&r=mac

Temi di Discussione

(Working Papers)

EAGLE-FLI. A macroeconomic model of banking

and financial interdependence in the euro area

by Nikola Bokan, Andrea Gerali, Sandra Gomes,

Pascal Jacquinot and Massimiliano Pisani

April 2016

Number

1064


Temi di discussione

(Working papers)

EAGLE-FLI. A macroeconomic model of banking

and financial interdependence in the euro area

by Nikola Bokan, Andrea Gerali, Sandra Gomes,

Pascal Jacquinot and Massimiliano Pisani

Number 1064 - April 2016


The purpose of the Temi di discussione series is to promote the circulation of working

papers prepared within the Bank of Italy or presented in Bank seminars by outside

economists with the aim of stimulating comments and suggestions.

The views expressed in the articles are those of the authors and do not involve the

responsibility of the Bank.

Editorial Board: Pietro Tommasino, Piergiorgio Alessandri, Valentina Aprigliano,

Nicola Branzoli, Ines Buono, Lorenzo Burlon, Francesco Caprioli, Marco Casiraghi,

Giuseppe Ilardi, Francesco Manaresi, Elisabetta Olivieri, Lucia Paola Maria Rizzica,

Laura Sigalotti, Massimiliano Stacchini.

Editorial Assistants: Roberto Marano, Nicoletta Olivanti.

ISSN 1594-7939 (print)

ISSN 2281-3950 (online)

Printed by the Printing and Publishing Division of the Bank of Italy


EAGLE-FLI. A MACROECONOMIC MODEL OF BANKING

AND FINANCIAL INTERDEPENDENCE IN THE EURO AREA

by Nikola Bokan*, Andrea Gerali**, Sandra Gomes***,

Pascal Jacquinot* and Massimiliano Pisani**

Abstract

We incorporate financial linkages into EAGLE, a New Keynesian multi-country dynamic

general equilibrium model of the euro area by including financial frictions and country-specific

banking sectors. In this new version, called EAGLE-FLI (Euro Area and Global Economy with

Financial Linkages), banks collect deposits from domestic household and cross-county interbank

markets and raise capital to finance loans to domestic households and firms. In order to borrow

from local (regional) banks, households use domestic real estate whereas firms use both

domestic real estate and physical capital as collateral. These features, together with a full

description of trade balance and real exchange rate dynamics and a broad array of financial

shocks, allow us to assess the domestic and cross-country macroeconomic effects of financial

shocks accurately. Our results support the views that (1) business cycles in the euro area can be

driven not only by real shocks but also by financial ones, (2) the financial sector could amplify

the transmission of (real) shocks and (3) financial/banking shocks and banking sectors can be

sources of business cycle asymmetries and spillovers across countries in a monetary union.

JEL Classification: E51, E32, E44, F45, F47.

Keywords: Banks, DSGE models, econometric models, financial frictions, open-economy

macroeconomics, policy analysis.

Contents

1. Introduction ......................................................................................................................... 5

2. The model ............................................................................................................................ 7

2.1 The banking sector ...................................................................................................... 8

2.2 Households ................................................................................................................ 11

2.3 Entrepreneur .............................................................................................................. 15

2.4 Firms .......................................................................................................................... 17

2.5 Monetary authority .................................................................................................... 19

2.6 Market clearing conditions ........................................................................................ 19

2.7 Net foreign asset position and international relative prices ...................................... 20

3. Calibration ......................................................................................................................... 22

4. Simulations ........................................................................................................................ 24

4.1 Reduction in the EA monetary policy rate ................................................................ 24

4.2 Increase in REA LTV ratio ....................................................................................... 25

4.3 Increase in Home banks lending in the interbank market ......................................... 26

4.4 Increase in the bank capital requirement ................................................................... 27

4.5 Sensitivity analysis .................................................................................................... 28

5. Conclusions ....................................................................................................................... 28

References .............................................................................................................................. 30

Tables and Figures .................................................................................................................. 32

Technical Appendix: Equations ............................................................................................. 56

_____________________

* European Central Bank.

** Bank of Italy.

*** Bank of Portugal.


1 Introduction 1

The recent financial crisis, which has resulted in a long period of economic stagnation and

extremely low inflation, especially in the euro area (EA), and the ensuing debate on policy

responses (in particular by central banks) have widely increased the need for understanding

how domestic and cross-country financial factors might affect macroeconomic performance in a

monetary union such as the EA. Cross-country heterogeneous conditions in financial markets

and banking sectors within the union can make it difficult for the common monetary policy to

guarantee the union-wide macroeconomic stability, while calling for macroprudential policies to

foster financial stability at a country and, hence, union level. Thus, understanding the role of

country-specific structural financial and banking features, their interaction within and across

regions and their effect on the transmission mechanism of monetary policy is crucial for a proper

analysis of monetary and financial stabilization issues in a monetary union, and in particular

for a thorough assessment of policy responses in the EA in the aftermath of the recent financial

crisis.

To tackle these issues we enrich a multi-country model of the EA called EAGLE (Euro Area

and GLobal Economy) model with financial frictions, banking sectors and a cross-country interbank

market. 2 This paper describes the new model setup, labeled EAGLE-FLI (Euro Area and

GLobal Economy with Financial LInkages), 3 and transmission mechanism via a set of simulations,

that shows the macroeconomic effects of several financial shocks, to illustrate its usefulness

from a policy perspective.

The original EAGLE model is a large-scale microfounded model developed for the analysis of

spillovers and macroeconomic interdependence across the different countries belonging to the EA

and between them and other countries outside the monetary union. The open economy version

of the New Keynesian paradigm, so called New Open Economy Macroeconomics framework,

constitutes EAGLE’s theoretical kernel and guarantees a nontrivial role for monetary, exchange

rate, fiscal and structural policy measures. The microfoundations of the model together with its

rich structure allow for a quantitative analysis in a theoretically coherent and fully consistent

model setup, clearly spelling out the policy implications. 4

EAGLE-FLI adds the following features to the original EAGLE framework. First, we introduce

two types of households, namely “borrowers”and “savers”. Second, we include a banking

1 We thank Günter Coenen for invaluable support. We thank two anonymous referees, participants at the

Working Group on Econometric Modeling, the EAGLE Network meetings, the 2015 DYNARE Conference. The

opinions expressed are those of the authors and do not reflect views of their respective institutions. Any remaining

errors are the sole responsibility of the authors.

2 See Gomes, Jacquinot and Pisani (2010, 2012) for the description of the standard EAGLE model.

3 Jointly developed by staff of Bank of Portugal, Bank of Italy, Croatian National Bank and European Central

Bank, EAGLE-FLI is a project of the EAGLE Network, under the auspices of the Working Group on Econometric

Modeling of the European System of Central Banks.

4 The EAGLE setup builds on the New Area Wide Model (NAWM, Coenen, McAdam and Straub, 2008). See

also the IMF’s Global Economy Model (GEM, Laxton and Pesenti, 2003 and Pesenti, 2008), the Bank of Canada’s

version of GEM (Lalonde and Muir, 2007), the Federal Reserve Board’s SIGMA (Erceg, Guerrieri and Gust, 2006),

the European Commission’s QUEST (Ratto, Roeger and in’t Veld, 2009), and IMF’s Global Integrated Monetary

Fiscal Model (GIMF, Kumhof and Laxton, 2007).

5


sector that intermediates credit flows (banking loans and deposits) in each of the four regions

of the model. Third, we introduce a real estate sector in the economy that provides housing

services to households, a stock of collateral to borrowers and that is used as an input in production.

In each region, a bank collects deposits from domestic savers, raises capital subject to

a regulatory requirement and lends both to domestic borrowing households and entrepreneurs,

subject to a collateral constraint written on their real estate holdings and, for entrepreneurs, also

on their physical capital. In addition, only banks located in the two EA regions have access to

an interbank market to exchange funds cross-country. Fourth, we enrich the model with a set of

financial shocks, such as shocks to the loan-to-value (LTV) ratio, the amount of resources that

banks desire to lend in the interbank market, and the bank capital requirement. The shocks are

simulated under perfect foresight, so households and firms perfectly anticipate their intertemporal

path, but not the value in the initial period (the “surprise”). We also report a sensitivity

analysis to further show the relevance of some key financial parameters for the transmission of

the shocks.

Our results aim at explaining the domestic and cross-country transmission mechanism of

various shocks in a monetary union model where financial factors do matter. Even though the

analysis does not aim to quantitatively explain neither the EA business cycle nor the recent

financial crisis, the results support the views that (1) the business cycles in the EA can be driven

not only by real shocks, but also by financial shocks, (2) the financial sector could amplify the

transmission of (real) shocks, and (3) the financial/banking shocks and the banking sectors can

be a source of business cycle asymmetries across countries in a monetary union.

The EAGLE-FLI setup builds on several earlier contributions. 5 The distinction between

borrowers, entrepreneurs and savers follows Iacoviello (2005). As in that contribution, we assume

that entrepreneurs and a fraction of households (the “borrowers”)are more impatient than

remaining households (the “savers”), i.e. the former have a lower discount rate than the latter.

Thus, the corresponding borrowing constraints are binding in the steady state and in its

neighborhood. The banking sector is akin to the one in Iacoviello (2015). 6

Regarding the capital requirement ratio, we follow Kollmann (2013) and Kollmann, Ratto

and Roeger (2013), and impose that in every period the bank capital should not be less than a

(possibly time-varying) fraction of the bank loans to domestic households and entrepreneurs in

the same period.

Kollmann (2013) and Kollmann, Ratto and Roeger (2013) consider the case of a global bank

lending domestically and abroad. Different from them, we do not have a “global” bank that

originates cross-border loans. Instead, we have country-specific banks that lend to and receive

deposits from domestic agents and that, in the case of EA blocs, lend to each other in the EA

5 In line with these contributions, we assume a cashless economy, so there is no explicit role for money. The

monetary policy rate, set according to a Taylor rule, is linked to the other interest rates, including the one

holding in the interbank market, via no-arbitrage conditions obtained from banks’, households’ and entrepreneurs’

maximization problems.

6 We follow Iacoviello (2015) and assume that entrepreneurs borrow against real estate and physical capital.

This is different from Iacoviello (2005), where both borrowers and entrepreneurs use real estate as collateral.

6


interbank market. Allowing banks to lend and borrow at international level is different from

allowing households to do the same, as they maximize different objectives subject to different

constraints, such as the capital requirement. EAGLE-FLI features financial spillovers that

directly affect banks behavior, and only indirectly (via banks) the foreign borrowers while in

Kollmann (2013) and Kollmann, Ratto and Roeger (2013) there is a direct spillover from bank

to foreign borrowers.

The “region-specific” banking sector setup is also used in Brzoza-Brzezina, Kolasa, and

Makarski (2015), who develop a monetary union model of the EA featuring two regional banking

sectors. Guerrieri, Iacoviello, and Minetti (2012) consider a two-region model calibrated to the

EA featuring regional banks and sovereign debt default. Different from these contributions, we

introduce a “region specific”banking sector in a large-scale open-economy New Keynesian dynamic

general equilibrium model. Thus, the model includes several ingredients needed for the

quantitative assessment of cross-country financial and banking spillovers in a monetary union. 7

The paper is organized as follows. Section 2 shows the setup of the banking and financial

sectors. Section 3 reports the calibration. Section 4 contains the results of simulating financial

shocks and the sensitivity analysis. Section 5 concludes.

2 The model

In this section we report the novel features that characterize the EAGLE-FLI setup. The model

features the world economy, whose size is normalized to one. It consists of four blocs (each bloc

represents a country or a region). s H ,s REA ,s US > 0 are respectively the sizes of Home, REA

and US blocs, and s H +s REA +s US < 1. For each bloc, the size of the economy corresponds to

the size of population (sum of households, bankers, entrepreneurs) and to the size of each firms’

sector (intermediate tradable, intermediate nontradable, final nontradable sectors). We assume

that two blocs, labelled Home (H) and rest of the EA (REA), are members of a monetary union,

the EA. Thus, they share the monetary policy authority and the nominal exchange rates against

the remaining two blocs, assumed to represent the U.S. (US) and the rest of the world (RW).

In what follows we focus on a description of the H bloc of the EA. We describe the banking

sector, households’ and entrepreneurs’ behavior, the monetary authority, market clearing conditions,

net foreign asset position and international relative prices. Other blocs are similar, so we

do not report the related equations to save on space. The exception is that the US and RW blocs

differ from those of the EA because their banking sectors do not lend/borrow in a cross-border

interbank market.

7 Gerali et al. (2010) estimate a model of the EA as a whole featuring a banking sector. Lombardo and

McAdam (2012) estimate a model of the EA as a whole with financial frictions.

7


2.1 The banking sector

The Home economy is populated by a continuum of banks that act under perfect competition

and, hence, maximize profits taking interest rates as given and choosing the optimal amount of

assets and liabilities. The banks are a fraction 0 < ω B < 1 of the H bloc population. They

have the same preferences, constraints and initial asset positions. Thus, they make the same

optimal choices and it is possible to assume a representative bank (the “bank”). The banking

sector intermediates funds between agents that cannot directly lend to and borrow from each

other (a crucial assumption for including the banking sector in a meaningful way in the model).

The bank finances loans to domestic impatient households (the “borrowers”) and to domestic

entrepreneurs by collecting deposits of domestic patient households (the “savers”) and raising

capital. Moreover, the Home bank takes a position in the (cross-country) EA interbank market.

Utility. The lifetime utility function of the representative bank is defined in terms of real

dividends

E t ∞ ∑

k=0

( ) 1−σ

(β B ) k 1 DIV

B

t+k

1−σ Pt+k

C , (1)

where E t is the expectation operator, 0 < β B < 1 is the discount factor, 1/σ > 0 is the intertemporal

elasticityof substitution, DIV B

t representsnominal dividends from banking intermediation

activity and P C t is the domestic private consumption deflator.

The budget constraint. Deposits, loans, and the position in the interbank market are all

defined as one-period euro-denominated nominal assets or liabilities. The bank’s nominal budget

constraint in period t is:

DIV B

t

= −L t +R L t−1 L t−1 −L IB

t +R IB

t−1 LIB t−1

+D Supply

t

−R D t−1D Supply

t−1

−P C t Γ L,t −P C t Γ IB,t −P C t Γ X,t, (2)

where L t denotes the amount of loans granted to domestic entrepreneurs and “borrowers”at the

predetermined gross interest rate R L t (it is paid at the beginning of period t+1 and it is known

in period t); 8 L IB

t is the amount of loans granted to the REA banking sector in EA interbank

market at the gross interest rate Rt IB ; D Supply

t denotes households deposits, that pay the gross

interest rate Rt D . The terms Γ L,t , Γ IB,t and Γ X,t are costs the bank faces when adjusting the

amount of loans granted, the position in the interbank market and the excess bank capital,

respectively. They are specified in “real”terms, i.e. in consumption units (so they are multiplied

by the consumption deflator P C t ). The “real”cost Γ L,t (in terms of consumption units) is defined

8 The same assumption holds for other interest rates.

8


in terms of changes in loans to allow for a gradual response to a given shock:

Γ L,t ≡ γ L

2

( ) 2 lt

−1 ,

l t−1

where γ L > 0 is a parameter, l t = Lt

(i.e. the amount of loans measured in consumption units).

Pt

C

The remaining costs will be defined below.

The interbank market. The H bank can borrow from or lend to the REA bank in the

EA interbank market, subject to the following “real” adjustment cost

Γ IB,t ≡ γ IB

2

(

l IB

t − κIB p Y Y

ω B

) 2

, (3)

where γ IB > 0 is a parameter and lt

IB ≡ LIB t

. The adjustment cost introduces a wedge between

Pt

C

the interest rate on interbank loans and the interest rate on deposits. p Y and Y represent the

steady-state output deflator (expressed in real terms, i.e. divided by the consumption deflator)

and real output, respectively. The parameter

κ IB ≡ ω B¯l IB

p Y Y

(4)

is the steady-state interbank aggregate loan-to-GDP ratio (where ¯l IB is the steady-state amount

of interbank loans by the representative H bank, measured in consumption units).

The interbank market is formalized in a rather stylized way. The model represents a cashless

economy (see Woodford, 1998) so we abstract from money and, hence, from interbank liquidity

as well. However,the introduction ofthis marketin the model allowsus to evaluatecross-country

spillovers directly associated with one regional bank’s behavior towards the other regional bank.

This is relevant in the light of the recent EA economic history, characterized by relevant changes

in the amount of cross-country interbank lending. In particular, introducing the interbank market

allows to get a bank-specific shock by exogenously shocking its position on this market via

the parameter κ IB . This can be interpreted as a change in the long-run “desired”amount of

interbank lending, that may be related to factors not formalized such as changes in liquidity

needs or attitude toward risk.

Capital requirement. As in Kollmann (2013), the bank faces a regulatory capital requirement,

i.e., its period t nominal capital

K B t = L t −D Supply

t

+L IB

t (5)

should not be less than a (possibly time-varying) fraction 0 < Υ K,t < 1 of its loans to domestic

9


householdsandentrepreneursinthesameperiod, L t . 9 Wedefinethenominalexcessbankcapital,

at the end of period t, as

X t ≡ (1−Υ K,t )L t −D Supply

t

+L IB

t . (6)

We assume it is costly, in terms of consumption units, for the bank to deviate from the long-run

(steady-state) value of excess bank capital, according to the following quadratic function: 10

Γ X,t ≡ γ X

2 (x t −x) 2 , (7)

where γ X > 0 is a parameter, x t ≡ Xt

is excess bank capital expressed in consumption units

Pt

C

and x is its steady-state value. This adjustment cost introduces a wedge between the interest

rate on domestic loans and the interest rate on deposits.

First order conditions (FOC). The representative bank maximizes lifetime utility (1) subject

to its budget constraint (2) and the cost from deviating from the capital requirement (7) (given

excess bank capital definition 6) with respect to dividends, deposit supply, loans supply and

interbank position. Variables are expressed in “real”terms by dividing them by the consumption

price deflator P C t (thus div B t ≡ DIV B

t /P C t ).

The implied FOC are:

• marginal utility of dividends Λ B,t

Λ B,t = ( div B t

) −σ;

(8)

• deposit supply

[ ]

Λ B,t = β B E t Λ B,t+1 Rt D Π−1 C,t+1

−Λ B,t γ X (x t − ¯x), (9)

where Π C,t+1 ≡ PC t+1;

Pt

C

• loans supply

[ ] ( ) [ (

Λ B,t = β B E t Λ B,t+1 Rt L lt 1

lt+1

Π−1 C,t+1

−γ L Λ B,t −1 +β B γ L E t Λ B,t+1 −1

l t−1 l t−1 l t

)

lt+1

−Λ B,t γ X (1−Υ K )(x t − ¯x); (10)

9 Bank capital requirements can limit moral hazard in the presence of informational frictions and deposit

insurance. We do not model this issue and take the capital requirement as given. Moreover, for simplicity, we

assume that interbank loans are not subject to the capital requirement.

10 In the steady-state equilibrium the capital requirement is satisfied with equality. Thus X = (1 − Υ K )L −

D Supply +L IB = K B −Υ K L ≥ 0.

l 2 t

]

10


• interbank loans

[

(

Λ B,t = β B E t Λ B,t+1 Rt IB Π −1

C,t+1

]−Λ B,t γ IB lt IB − κIB p Y )

Y

−Λ B,t γ X (x t − ¯x). (11)

ω B

2.2 Households

The Home economy is populated by a continuum of two types of households: patient (“savers”)

and impatient (“borrowers”). I-type households are patient while J-type are impatient households.

The savers are a fraction (1−ω J −ω E −ω B ) of the H population, where ω J and ω E

(ω J ,ω E > 0, ω J + ω E + ω B < 1) are the shares of impatient households and entrepreneurs in

the H population, respectively. Within each type, agents have the same preferences, constraints

and initial asset positions. Each household offers a differentiated labor service to domestic firms

and acts as wage setter, under monopolistic competition. Each nominal wage is set according to

a Calvo-type mechanism (Calvo, 1983). It is assumed there is perfect wage risk-sharing across

households of the same type. Thus, it is possible to assume a representative patient household

and a representativeimpatient household(there is also a representativeentrepreneur, asreported

in Section 2.3). These two types of households differ in terms of their discount factors, whereby

patient households’ discount factor is larger than that of impatient households (β I > β J ). Thus,

in equilibrium, impatient households are net borrowers while patient households are net lenders

vis-à-vis the domestic bank. 11 Both types of households consume and work. Savers have access

to multiple financial assets while constrained households can only borrow from the domestic

banking sector.

Patient household (“Saver”)

Utility. The representative patient household, labelled “saver”, gets utility from consumption

of the nondurable composite good, C I,t (subject to external habit formation) and from housing

services H I,t and gets disutility from working N I,t

[ ∞

(


( ) )]

1−σ

E t (β I ) k 1−κ CI,t+k −κC I,t+k−1

+ι I lnH I,t+k − 1

1−σ 1−κ

1+ζ N1+ζ I,t+k

, (12)

k=0

where 0 < β I < 1 is the discount factor, 0 ≤ κ ≤ 1 measures the degree of external habit formation

in consumption, σ > 0 denotes the inverse of the intertemporal elasticity of substitution,

ι I > 0 is a parameter for utility from housing services and ζ > 0 is the inverse of the elasticity

of work effort with respect to the real wage (Frisch elasticity).

Budget constraint. The patient household provides work to firms in the two intermediate

goods production sectors under monopolistic competition and sets wages W I,t in a staggered

11 For discount factor heterogeneity, see Iacoviello (2005).

11


way, à la Calvo (1983) with indexation. 12 She holds positions in euro-denominated domestic

sovereign bonds, in internationally traded US dollar-denominated bonds and euro-denominated

bonds (the last assumption holds only for households in the two EA blocs). She also deposits in

the domestic bank. The nominal budget constraint is:

D Dem

t

+S H,US

t Bt

US

−R D t−1D Dem

t−1 +B I,t −B I,t−1 R t−1 +B EA

I,t −B EA

I,t−1R t−1

−S H,US

t Bt−1 US RUS t−1

= (1−τ N,t −τ Wh ,t)W I,t N I,t +(1−τ D,t )DIV F

t −Q H t (H I,t −(1−δ H )H I,t−1 )

−(1+τ C,t )P C t C I,t −P C t Γ DH,t +TR t −T t , (13)

where Dt

Dem is demand for bank deposits; B I,t is the position in the domestic government

bonds, traded only domestically between patient household and the government and paying the

EA (gross) monetary policy rate R t ; BI,t EA is the position in the euro-denominated bond, traded

between EA patient households and paying the EA monetary policy rate R t ; Bt

US is holdings of

bonds denominated in US dollars, paying the (gross) interest rate Rt US , set by the US central

bank, and converted in euro currency by the Home nominal exchange rate relative to the US,

S H,US

t (euro per unit of US dollar). 13 For income, W I,t N I,t is labor income (0 < τ N,t , τ Wh ,t < 1

represent tax rates on labor and payrolls, respectively, both possibly time-varying); DIV F is

income from ownership of domestic firms (other than banks) and 0 < τ D,t < 1 the related tax

rate. For expenditures, Q H t is the price of housing (0 < δ H < 1 is the depreciation rate of

the housing stock, as housing is formalized as a durable good), 0 < τ C,t < 1 is tax rate on

(nondurable) consumption good, and Γ DH is the cost of adjusting deposits, which is defined as

where d Dem

t

≡ DDem t

Pt

C

Γ DH,t ≡ γ DH

2

and

(

d Dem

t −κ D p Y Y

1−ω J −ω E −ω B

) 2

, (14)

κ D ≡ (1−ω J −ω E −ω B )

p Y Y

¯d

Dem

is the steady-state deposit-to-GDP, where (1−ω J −ω E −ω B ) ¯d Dem are per capita aggregate

deposits and p Y Y is per capita aggregate output, both computed in steady state and expressed

in consumption units. Finally, the terms TR t and T t represent (gross) lump-sum transfers and

taxes respectively. They are set, together with public spending and tax rates, by the domestic

fiscal authority.

(15)

FOC. The household maximizes her lifetime utility subject to the budget constraint taking

all prices but wages as given. All nominal variables in the budget constraint are expressed in

12 For details see Gomes, Jacquinot and Pisani (2010, 2012).

13 As standard in the literature, we add an adjustment cost to the interest rate paid by the US bond so to make

the bond position (and, hence, the model) stationary.

12


“real” terms by dividing them by the consumption price deflator P C t . Focusing on the new

features of the model, namely housing and bank deposits, we obtain the following FOC:

• marginal utility of consumption Λ I,t

• deposits demand

( ) −σ CI,t −κC I,t−1

Λ I,t (1+τ C ) = ; (16)

1−κ

[

(

Λ I,t = β I E t Λ I,t+1 Rt D Π−1 C,t+1

]−Λ I,t γ DH d Dem κ D p Y )

Y

t − ; (17)

1−ω J −ω E −ω B

• real estate demand (where q H t ≡ Q H t /PC t )

Λ I,t qt H = ι I [

+β I E t ΛI,t+1 (1−δ H )q H ]

t+1 . (18)

H I,t

2012).

The remaining FOC are standard. They are reported in Gomes, Jacquinot and Pisani (2010,

Impatient household (“borrower”)

Utility. The representative impatient household represents a fraction ω J of the H population.

Her discount factor is smaller than those of the patient household and the bank. This makes her,

in equilibrium, borrower vis-à-vis the domestic bank. The impatient household lifetime utility

function is:

[ ∞

(


( ) )]

1−σ

E t (β J ) k 1−κ CJ,t+k −κC J,t+k−1

+ι J lnH J,t+k − 1

1−σ 1−κ

1+ζ N1+ζ J,t+k

, (19)

k=0

where 0 < β J < β I < 1 and consumption is subject to external habit.

Budget constraint. The impatient household provides work to firms in the two intermediate

goods production sectors under monopolistic competition and sets wages W J,t in a staggered

way, à la Calvo(1983)with indexation. 14 She gets lump-sum transfersfrom the domestic government,

TR J /ω J , where TR J are aggregate nominal transfers. The (nominal) budget constraint

is:

B J,t −R L t−1B J,t−1 = (1−τ N,t −τ WH,t )W J,t N J,t

− (1+τ C,t )Pt C C J,t −Q H t (H J,t −(1−δ H )H J,t−1 )−Pt C Γ B J,t + TR J

(20) ,

ω J

14 For details see Gomes, Jacquinot and Pisani (2010, 2012).

13


where B J,t < 0 is the amount of loans from domestic bank and R L t is the interest rate, and Γ BJ

is the “real” adjustment cost on changing the borrowing position,

Γ BJ,t ≡ γ B J

2

( ) 2 bJ,t

−1 , (21)

b J,t−1

with γ BJ > 0 and b J,t ≡ BJ,t

.

Pt

C

Borrowing constraint. To borrow funds, the household needs collateral, represented by the

expected value of her housing stock. Therefore, she faces the following borrowing constraint

−B J,t R L t ≤ −ρ BJ ΠB J,t−1 R L t−1 +(1−ρ BJ )V J,t E t

[

Q

H

t+1 H J,t

]

, (22)

where 0 < ρ BJ < 1 is a parameter capturing inertia in changing the borrowing limit as in

Iacoviello (2015), Π is the steady-state inflation (needed to properly calibrate the steady-state

debt and, at the same time, satisfy the borrowing constraint) and 0 < V J,t < 1 is the (possibly

time-varying) LTV ratio. The borrowing constraint is consistent with standard lending criteria

used in the mortgage market, which limit the amount lent to a fraction of the value of the asset.

FOC. The impatient household maximizes utility with respect to consumption of nondurables,

housing and loans subject to the budget constraint and the borrowing constraint and taking all

prices, but wages, as given. The reason is that the impatient household supplies labor under

monopolistic competition. Thus, she optimally sets her nominal wage taking labor demand by

firms into account. The borrowing constraint holds with equality (see Iacoviello, 2005). The

household’ consumption is subject to external habit formation. All nominal variables in the budget

constraint and in the borrowing constraint are expressed in “real” terms by dividing them

by the consumption price deflator Pt C .

Focusing on the new features of the model, we obtain the following FOC:

• marginal utility of consumption of nondurable goods Λ J,t

• loans demand

( ) −σ CJ,t −κC J,t−1

Λ J,t (1+τ C ) = ; (23)

1−κ

[ ]

Λ J,t = β J E t Λ J,t+1 Rt L Π −1

C,t+1

( ) [ (

bJ,t 1

bJ,t+1

− γ BJ Λ J,t −1 +β J γ BJ E t Λ J,t+1 −1

b J,t−1 b J,t−1 b J,t

+ R L t Λ JC,t −ρ BJ Πβ J E t

[

Λ JC,t+1 R L t Π −1

C,t+1

)

bJ,t+1

b 2 J,t

]

; (24)

]

14


• real estate demand

Λ J,t qt H = ι J [

+β J E t ΛJ,t+1 (1−δ H )q H ] [ ]

t+1 +(1−ρBJ )Λ JC,t V J,t E t q

H

H t+1 Π C,t+1 , (25)

J,t

where Λ JC,t is the Lagrange multiplier of the borrowing constraint. The borrowing constraint

affects the optimal choices of borrowing and housing services (equations 24 and 25, respectively).

The multiplier equals the increase in lifetime utility that would stem from borrowing Rt L euros,

consuming or investing the proceeds, and reducing consumption by an appropriate amount the

following period.

2.3 Entrepreneur

Utility. The representative entrepreneur represents a fraction ω E of the H population. She

maximizes lifetime utility represented by

(


∞ ( ) ) 1−σ

E t (β E ) k 1−κ CE,t+k −κC E,t+k−1

, (26)

1−σ 1−κ

k=0

where consumption of nondurable goods is subject to external habit.

Budget constraint. The entrepreneur owns the physical capital stock and part of the aggregate

domestic stock of real estate. Both are rented in a competitive market to firms operating

in the domestic intermediate sectors. Entrepreneurscan borrow funds from domestic banks. The

investment in physical capital is subject to adjustment costs. The budget constraint reads as

B E,t −Rt−1B L E,t−1 = R H,t H E,t−1 +(1−τ K,t ) ( R K,t u t −Γ u,t Pt

I )

KE,t−1 +τ K,t δ K Pt I K E,t

− Q H t (H E,t −(1−δ H )H E,t−1 )−(1+τ C,t )Pt C C E,t −Pt I I E,t

− Pt C Γ B E,t, (27)

where B E,t < 0 is the amount of loans from domestic bank, R H,t and R K,t are the rental rates

of real estate H E,t and physical capital K E,t to firms in the intermediate sector, respectively.

The variable u t stands for capital utilization and Γ u,t stands for the corresponding adjustment

cost. The variable 0 < τ K,t < 1 is the tax rate on physical capital, set by the domestic fiscal

authority. The parameters 0 < δ K ,δ H < 1 are the depreciation rates of capital and real estate,

respectively. The variable I E,t is the investment in physical capital, whose price is Pt I . The term

Γ BE represents the “real” adjustment cost on changing the borrowing position, defined as

Γ BE ,t ≡ γ B E

2

( ) 2 bE,t

−1 , (28)

b E,t−1

with γ BE > 0 and b E,t ≡ BE,t

.

Pt

C

15


Investment is subject to adjustment costs, namely

K E,t = (1−δ K )K E,t−1 +(1−Γ I,t )I E,t , (29)

where Γ I,t is the adjustment cost formulated in terms of changes in investment:

with γ I > 0.

Γ I,t ≡ γ I

2

( ) 2 IE,t

−1 , (30)

I E,t−1

Borrowing constraint. The entrepreneur borrows funds B E,t from the domestic banking

sector using the owned real estate and physical capital as collateral:

−Rt L B E,t ≤ −ρ BE ΠB E,t−1 Rt−1 L +(1−ρ [ ] [ ]

B E

)V HE,tE t Q

H

t+1 H E,t +(1−ρBE )V KE,tE t Q

K

t+1 K E,t ,

(31)

where 0 < ρ BE < 1 is a parameter that captures inertia in changing the borrowing position

and 0 < V HE,t,V KE,t < 1 are the (possibly time-varying) entrepreneur’s LTV ratios associated

with real estate and physical capital, respectively. Finally, Q K is the Tobin’s Q, i.e. the price of

capital, which is different from one because of the adjustment costs on investment change.

FOC.Theentrepreneurmaximizesherutilitywith respecttoconsumptionofnondurablesgoods,

investment in physical capital, physical capital, and housing, subject to the budget constraint

and the borrowing constraint, and taking prices as given. All nominal variables in the budget

constraint and in the borrowing constraint are expressed in “real” terms by dividing them by the

consumption price deflator Pt C . In particular, p I t ≡ Pt I /Pt C , r H,t ≡ R H,t /Pt C , r K,t ≡ R K,t /Pt C ,

qt K ≡ Q K t /PC t . The FOC related to EAGLE-FLI novel features are:

• consumption of nondurable goods

( ) −σ CE,t −κC E,t−1

Λ E,t (1+τ C,t ) =

; (32)

1−κ

• investment in physical capital

p I t

= q K t

(

1−ΓI,t −Γ ′ I,t I E,t)

[

]

Λ E,t+1

+β E E t q K I

t+1

Λ Γ′ E,t+1

2

I,t+1 ; (33)

E,t I E,t

16


• physical capital demand

Λ E,t q K t = β E E t

[

ΛE,t+1 (1−τ K,t ) ( r K,t+1 u t+1 −Γ u,t+1 p I t+1)]

+τK,t δ K p I t

+ β E E t

[

ΛE,t+1 q K t+1(1−δ H ) ] +(1−ρ BE )Λ EC,t V KE,tE t

[

q

K

t+1 Π C,t+1

]

;(34)

• real estate demand

Λ E,t q H t = β E E t

[

ΛE,t+1 r H,t+1 +Λ E,t+1 (1−δ H )q H t+1]

+(1−ρBE )Λ EC,t V HE,tE t

[

q

H

t+1 Π C,t+1

]

;

• loans demand

[ ]

Λ E,t = β E E t Λ E,t+1 Rt L Π−1 C,t+1

( ) [ (

bE,t 1

bE,t+1

− γ BE Λ E,t −1 +β E γ BE E t Λ E,t+1 −1

b E,t−1 b E,t−1 b E,t

+ Λ EC,t R L t +β Eρ BE ΠE t

[

Λ EC,t+1 R L t Π−1 C,t+1

)

bE,t+1

b 2 E,t

(35)

]

, (36)

]

where Λ E,t is the Lagrange multiplier of the entrepreneurs’ budget constraint and Λ EC,t is the

Lagrange multiplier of the entrepreneurs’ borrowing constraint. Like for impatient households,

the equations for consumption and housing choice hold with the addition of the multiplier associated

with the borrowing restriction. The borrowing constraint introduces a wedge between

the price of the real estate and its rental rate. It can be considered as a tax on the demand for

credit and for real estate.

2.4 Firms

There are two types of firms. One type produces intermediate goods, either internationally

tradable or nontradable. The other type produces nontradable final goods for consumption and

investment purposes, using all intermediate goods as inputs.

Final good firms

Firms producing final nontradable goods are symmetric, act under perfect competition and use

nontradable as well as domestic and imported tradable intermediate goods as inputs. The size

of the sector is s H . The intermediate goods are assembled according to a constant elasticity

of substitution (CES) technology. Final goods can be used both for private consumption and

investment. The setup of the final good firms mimics the one in the version of the EAGLE model

without financial frictions and a banking sector (see Gomes, Jacquinot and Pisani 2010, 2012).

17


Intermediate good firms

There are firms producing tradable and nontradable intermediate goods (brands) under a monopolistic

competition regime. Each tradable brand is produced by a firm h belonging to the

continuum of mass s H (h ∈ [ 0,s H) ). Similarly, each nontradable brand is produced by a firm n,

defined over the continuum of mass s N (n ∈ [ 0,s H) ). Since the EAGLE-FLI model introduces

a new input in production compared to the original EAGLE model, we will describe the intermediate

goods sector setup in more detail.

Production technology. Each nontradable and tradable intermediate good, respectively n

and h, is produced using a Cobb-Douglas technology with three inputs: physical capital rented

from domestic entrepreneurs (K D t (n) and K D t (h)); domestic labor (N D t (n) and N D t (h), each

being an aggregate of both patient and impatient households labor services); real estate (H D t (n)

and H D t (h)) rented from domestic entrepreneurs

Y S,N

t = z N,t

(

K

D

t

) αKN (

H

D

t

) αHN (

N

D

t

) 1−αKN−α HN

, (37)

Y S,T

t = z T,t

(

K

D

t

) αKT (

H

D

t

) αHT (

N

D

t

) 1−αKT−α HT

, (38)

where α KN ,α KT ,α HN ,α HT > 0, α KT + α HT < 1, and α KN + α HN < 1. z N,t and z T,t are

sector-specific productivity shocks (they are identical across firms within each sector). 15

Taking input prices as given, firms in each sector minimize total production costs subject to

the respective production function (equations 37 and 38). This yields standard demand functions

for each type of input (see the Technical Appendix). Finally, the labor bundle of the generic firm

n in the nontradables sector is defined as

N D t (n) =

[ (1−ωJ ) 1 (

η

−ω E −ω B N

D

1−ω E −ω I,t (n) η−1

η

+

B

) 1

ω J

1−ω E −ω B

η

N

D

J,t (n) η−1

η

] η

η−1

, (39)

where η > 0 is the elasticity of substitution between the two household-specific labor bundles,

NI,t D (n) and ND J,t (n). This yields the following demand functions:

N D I,t(n) = 1−ω J −ω E −ω B

1−ω E −ω B

(

WI,t

W t

) −η

N D t (n), (40)

N D J,t(n) =

ω J

1−ω E −ω B

(

WJ,t

W t

) −η

N D t (n), (41)

where W t is

W t =

[( ) (

1−ωJ −ω E −ω B

W 1−η

I,t

+

1−ω E −ω B

)

ω J

W 1−η

J,t

1−ω E −ω B

] 1

1−η

. (42)

15 In the case of the EA there is also a technology shock z t, which is common to both sectors and regions.

18


Similar bundles and demand functions hold for firms in the tradables sector.

Price setting. Each firm sells its differentiated output under monopolistic competition. The

firm producing the tradable intermediate good charges different prices in local currency at home

and in each foreign region. There is sluggish price adjustment due to staggered price contracts

à la Calvo (1983). Firm h in the intermediate tradables sector discriminates across countries,

by invoicing and setting the price of its brand in the currency of the generic destination market.

Hence, the local currency pricing assumption holds. For details on the price setting equations

see Gomes, Jacquinot and Pisani (2010, 2012).

2.5 Monetary authority

In the case of the EA, there exists a single monetary authority that targets a weighted (by

regional size) average of regional (Home, H, and REA) annual consumer price inflation and real

quarterly output growth:

(

R

EA

t

) 4

= φ EA

R

+φ EA

gY

) 4 ( ) [

+ 1−φ

EA

R

(R EA) 4 (


EA

Π Π EA,4

C,t

−Π EA,4)]

(

Y

EA

gr,t −1 ) +ε EA

R,t, (43)

(

R

EA

t−1

where Π EA,4 is the long-run(yearly)inflationtarget andthe yearlyinflation rateΠ EA,4

C,t

is defined

as

with

Π EA,4

C,t

(


Π H,4

C,t

) s H

s H +s REA ( Π REA,4

C,t

Π H,4

C,t ≡ PH C,t

PC,t−4

H , Π REA,4

C,t

and the EA output growth rate Y EA

gr,t is defined as

) s REA

s H +s REA , (44)


PREA C,t

PC,t−4

REA , (45)

gr,t ≡ Y t

EA

Y EA

Yt−1

EA

≡ sH Yt H +s REA Yt

REA

s H Y H

t−1 +sREA Yt−1

REA

, (46)

where Yt

H and Yt

REA represent per capita total final real output in the H and REA regions,

respectively. They are weighted by the corresponding regional sizes in the world economy.

2.6 Market clearing conditions

In this section, we report clearing conditions for the housing, loans, deposits, EA cross-country

interbank markets.

• Housing market. Households and entrepreneurs demand real estate, which is assumed

19


to be nontradable across countries and in fixed (per capita) aggregate supply ¯H

(1−ω J −ω E −ω B )H I,t +ω J H J,t +ω E H E,t = ¯H. (47)

Entrepreneurs rent housing to firms producing intermediate tradable and nontradable

goods:

H T t +H NT

t = ω E H E,t , (48)

where

H T t = 1

s H ∫ s

H

0

H D t (h)dh, H N t = 1

s H ∫ s

H

0

H D t (n)dn. (49)

• Loans market. Bankerssupplyloanstodomesticentrepreneursandimpatienthouseholds:

ω B L t +ω J B J,t +ω E B E,t = 0. (50)

• Deposits market. Patient households demand bank deposits to domestic banks:

ω B D Supply

t

= (1−ω J −ω E −ω B )D Dem

t . (51)

• EA cross-country interbank market. The two EA regional banks lend each other

resources through the EA interbank market. The market clearing is:

s H ω H B LIB,H t

+s REA ωB

REA L IB,REA

t = 0, (52)

where L IB,H

t

and L IB,REA

t

are the positions of Home and REA regions, respectively.

2.7 Net foreign asset position and international relative prices

Home holdingsofforeignbonds per capita (that is, the Home economy’snet foreignassetposition

in per capita terms), denominated in US dollars, evolve according to

L IB

t

(1−ω J −ω E −ω B )B US,t +ω B

S H,US

t

+(1−ω J −ω E −ω B ) BEA I,t

S H,US

t

L IB

t−1 +ω B

(1−ω J −ω E −ω B )B US,t−1 R US

+(1−ω J −ω E −ω B ) BEA I,t−1 R t−1

S H,US

t

where TB H t stands for Home trade balance per capita, defined as

TB H t ≡ ∑

s CO

s H SH,CO t

CO≠H

=

t−1Rt−1

IB

S H,US

t

+ TBH t

S H,US

t

, (53)

P H,CO

X,t

IM CO,H

t − ∑

P H,CO

IM,t IMH,CO t , (54)

CO≠H

20


where S H,CO

t is the bilateral nominal exchange rate of the Home country relative to country CO

(euro per unit of country CO currency), IM CO,H

t is Home exports (P H,CO

X,t

is the corresponding

price index in foreign currency), IM H,CO

t

index in euro terms).

is Home imports (P H,CO

IM,t

is the corresponding price

The market clearing conditions, jointly with the budget constraints of the households, entrepreneurs,

banking sector and the fiscal authority, imply the following resource constraint in

per capita terms

P Y,t Y t = P C,t C t +P I,t (I t +Γ u,t K t )+P G,t G t + ∑

− ∑

CO≠H

− ∑

CO≠H

P H,CO

IM,t

P H,CO

IM,t

(

(

IM H,CO

C,t

IM H,CO

I,t

)

1−Γ H,CO

IM C

Γ H,CO†

IM C

s CO

s H SH,CO t

CO≠H

P H,CO

X,t

IM CO,H

t

)

1−Γ H,CO

IM I

Γ H,CO† , (55)

IM I

where G t is public consumption and P G,t the corresponding price deflator, and consumption in

per capita terms, C t , is

and

C t ≡ ω B C B,t +(1−ω J −ω E −ω B )C I,t +ω J C J,t +ω E C E,t , (56)

C B,t

≡ DIV t

B

Pt

C , (57)

and Γ H,CO

IM C

I t ≡ ω E I E,t , (58)

K t ≡ ω E K E,t , (59)

is a (standard) adjustment costs on imports and Γ H,CO†

IM C is defined as 16

Γ H,CO†

IM C

(

≡ 1−Γ H,CO

IM C

) ( (

IM C,CO

t

Q C − Γ H,CO

IM C

t

))

IM C,CO ′

t

Q C IMt C .

t

The Home bilateral terms of trade relative to the generic country CO are defined as the Home

price of imports relative to the price of Home exports, both expressed in Home currency:

TOT H,CO

t


S H,CO

t

P H,CO

IM,t

P H,CO

X,t

. (60)

The Home bilateral real exchange rate relative to the generic country CO is defined as the CPI

16 See Gomes, Jacquinot and Pisani (2010) for more details.

21


of country CO relative to the CPI of country H, both expressed in Home currency:

3 Calibration

RER H,CO

t

≡ SH,CO t

P H C,t

P CO

C,t

. (61)

We calibrate at the quarterly frequency the model blocs to Germany (Home country, as in

the standard EAGLE), REA, US and RW. We set a subset of model parameters to match the

(usual) “great” ratios and the banking variables (as a ratio to GDP). The remaining parameters

are calibrated in line with the literature, in particular with the calibration of models such as

EAGLE, GEM and NAWM.

Table 1 reports banks’ balance sheet, as a ratio to annualized GDP. The data is taken from

Eurostat Annual Sector Accounts and the Federal Reserve Board Financial Accounts (and refer

to nominal outstanding amounts at the end of the year divided by annual nominal GDP). Given

the lack of available data on collateralized loans for other purposes but housing, we choose to

match the average share (over the 1999-2013 period) of total loans to households, namely to

64% for Germany; 61% for the REA; 90% for the US; 76% for the RW. We assume that the

steady-state (EA) interbank position is zero. Given the matched values for loans to households,

the assumed interbank position, the assumed zero excess bank capital in the steady state, the

calibration of the capital requirement and the entrepreneurs’ LTV ratios (see below), we allow

deposits to endogenously adjust consistently with the bank’s balance sheet. This calibration

strategy emphasizes the role of bank’s loans and thus induces a broad interpretation of bank

deposits (given the absence of other financing sources such as bank bonds in the model).

Table 2 reports the matched great ratios. National accounts data for the EA regions and

the US are taken from Eurostat. We set region sizes to match the share of world GDP (IMF

data). The sources of EA and of US net foreign asset position data are Eurostat and Bureau of

Economic Analysis, respectively. 17

Table3reportstheparametersrelatedtofinancialfrictionsandbankingsector. Theimpatient

households’ LTV ratio is set to 0.7 in both EA regions, in line with the calibration of the EA

households LTV ratio in Lombardo and McAdam (2012) and the calibration of Calza, Monacelli

and Stracca (2013) for Germany. The entrepreneurs’ LTV ratio associated with housing as

collateral is also set to 0.7, while the LTV ratio associated with capital is set to 0.30, in line with

the literature. Both adjustment costs on excess bank capital and on the EA interbank position

are set to 0.001 in all blocs. The adjustment cost on deposits is set to 0.0001. We set adjustment

costs to a rather low value to limit their role for the dynamics of the model, while, at the same

time, preserving the model stationarity. As for the adjustment costs on changes in loans, we set

the corresponding parameters both for the banks and the borrowers (impatient households and

17 Given the import shares, net foreign asset position and international interest rate, the steady-state trade

balance and real exchange rate level endogenously adjust. The RW is obtained as a residual.

22


entrepreneurs) to 1.5. Finally, the capital requirement parameter is set to 8% in the EA and the

US, consistent with the BASEL III minimum requirement for total capital.

Table4reportspopulationshares,preferenceandtechnologyparameters. Theshareofpatient

households in each region is set to 30%, the share of impatient households to 0.50 while the share

of entrepreneurs is set to 0.10 (as reported in Table 3, the share of bankers is set to 10%).

Preferences are assumed to be the same across household types and regions. We set the

discount factor of patient households to 0.9926 (implying a steady-state annualized real interest

rate of about 3%). The discount factor of impatient households, entrepreneurs and bankers

(the latter is reported in Table 3) are set to 0.96, 0.99 and 0.9926, respectively. 18 The habit

persistence parameter, the intertemporal elasticity of substitution and the Frisch elasticity are

respectively set to 0.70, 1 and 0.50. We set quarterly depreciation rate of capital to be consistent

with a 10% annual depreciation rate. The annual depreciation rate for the housing stock is set

at a lower value than that for capital, to 4%.

On the production side, in the Cobb-Douglas production functions of tradable and nontradable

intermediate goods the bias towards capital is set to around 0.30 and the bias towards

housing to 0.01 in both tradable and nontradable sectors. As for the final goods baskets, the

degree of substitutability between domestic and imported tradables is higher than that between

tradables and nontradables, consistent with existing literature (elasticities equal to 2.5 and 0.5,

respectively). 19 The biases towards the tradable bundle in the consumption and investment

baskets are equal respectively to 0.45 and 0.75 in each region of the EA and respectively to

0.35 and 0.75 in the US and RW. The weight of domestic tradable goods in the consumption

and investment tradable baskets is different across countries, to be coherent with multilateral

import-to-GDP ratios.

Markups in the EA nontradables sector (a proxy for the services sector) and labor market

are higher than the corresponding values in the US and RW (see Table 5). In all regions the

markup in the tradables sector (a proxy for the manufacturing sector) has the same value and

the markup in the nontradables sector is higher than that in the labor market. 20

Table 6 reports nominal and real rigidities. We set Calvo price parameters in the domestic

tradablesandnontradablessectorto0.92(12.5quarters)intheEA,consistentlywithestimatesby

Christoffel, Coenen, and Warne (2008) and Smets and Wouters (2003). Corresponding nominal

rigidities outside the EA are equal to 0.75, implying an average frequency of adjustment equal

to 4 quarters, in line with Faruqee, Laxton, and Muir (2007). Calvo wage parameters and price

18 Following Iacoviello (2015) a necessary condition for entrepreneurs to be constrained is that their discount

factor is lower than the inverse of the return on loans. When this condition is satisfied entrepreneurs will be

constrained in a neighborhood of the steady state. Similarly, banks are “credit-constrained” by their capital

requirement (which holds as strict equality in a neighborhood of the steady state) as long as their discount factor

is lower than the returns on deposits.

19 Note that the short-run elasticity for imported goods is lower because of adjustment costs on imports. Numbers

are consistent with Bayoumi, Laxton, and Pesenti (2004).

20 The chosen values are consistent with estimates from Martins, Scarpetta and Pilat (1996), suggesting that

the degree of competition in the nontradables sector is lower than in the tradables sector. Also, these values are in

line with other similar studies, such as Bayoumi, Laxton, and Pesenti (2004), Faruqee, Laxton, and Muir (2007)

and Everaert and Schule (2008).

23


parameters in the export sector are equal to 0.75 in all the regions. The indexation parameters

on prices and wages are equal respectively to 0.50 and 0.75, so to get sufficiently hump-shaped

response of wages and price. For real rigidities, we set adjustment costs on investment changes

to 6 in the EA and to 4 in the case of the US and RW; and adjustment costs on consumption

and investment imports to 2 and 1, respectively.

We set weights of bilateral imports on the bundles to match the trade matrix reported in

Table 7. 21

Table 8 reports parameters in the monetary policy rules and fiscal rules. The interest rate

reacts to its lagged value (inertial component of the monetary policy), annual inflation and

quarterly output growth. In the monetary union, monetary policy reacts to EA-wide variables.

For fiscal rules, lump-sum taxes stabilize public debt. Steady-state ratios of government debt

over output are equal to 2.40 in all the regions (0.6 in annual terms). Tax rates are set to be

consistent with empirical evidence (see Coenen, McAdam, and Straub 2008).

4 Simulations

In what follows we report the effects of several shocks to show the main transmission channels

operating in EAGLE-FLI. Specifically, we report a reduction in the EA monetary policy rate, an

increase in the Home LTV ratio, an increase in the long-run amount of interbank lending by the

Home bank, a simultaneous increase in the capital requirement ratio in both Home and REA

regions. The model is simulated under perfect foresight using DYNARE. 22

4.1 Reduction in the EA monetary policy rate

Figures 1a-1d show the implications of a monetary policy shock in the EA. The shock is such

that there is an initial decline in the (annualized) short-term nominal interest rate of 25 basis

points.

Figure 1a reports the response of the banking sector variables. Bank choices are dictated by

the no-arbitrage conditions implicitly given by their FOC with respect to the different financial

assets and liabilities. The decrease in the monetary policy rate is transmitted to interest rates on

bank loans and bank deposits, that also decrease. Lending to domestic (impatient) households

and entrepreneurs increases, financed by the increase in deposits (patient households smooth

consumption, and thus increase their savings). Also, bank capital slightly falls. The Home bank

decreases its lending to REA bank through the interbank market to a rather small extent.

Figure 1b reports the responses of borrowing and housing variables. In both regions, the impatient

household and the entrepreneur increase their borrowing and their demand for housing,

which they use as collateral. Higher demand by the impatient household and the entrepreneur

21 The trade matrix is calibrated using Eurostat and IMF trade statistics.

22 We report in the Technical Appendix new equations as they appear in the code, i.e. in real terms. Other

equations are the same as in Gomes, Jacquinot and Pisani (2010), see the Appendix therein for details.

24


induces the increase in the housing price, which reinforces the impact of the shock by allowing

higher borrowing against the housing stock. Firms operating in both the tradables and

nontradables sectors increase their demand for rented housing as well, to increase production.

Figure 1c shows that the impact of the shock on main macroeconomic variables (GDP, GDP

components and CPI inflation) is, as expected, expansionary. The consumption increase is in

line with that of GDP while investment increases by more. The higher EA aggregate demand

leads to an increase in imports. Exports also increase, favored by the depreciation of the real

exchange rate. 23 The REA GDP increases slightly more than Home GDP does, as REA has

a larger home bias than Home, i.e. a larger share of REA aggregate demand is satisfied by

domestic production. Consistent with the lower home bias, Home imports increase more than

REA imports, while Home exportsincrease morebecause ofthe largerincreasein REAaggregate

demand.

As reported in Figure 1d, consumption and labor by both types of households increase.

Consumption of impatient households rises by a rather larger extent since the increase in house

prices loosens the collateral constraint (despite the smaller unexpected rise in inflation). Real

wages of impatient and patient households also increase, driven by the higher labor demand by

domestic firms.

Spillovers to the US and the RW are rather small. To save on space, we do not report them.

Overall, the banking sector transmits the monetary policy stimulus to the real side of the

economy, favoring an increase in EA economic activity. The impact of the common monetary

policy shock is rather similar across the two EA regions.

4.2 Increase in REA LTV ratio

Figures 2a-2d show the effects of a change in lending standards applied by banks to their customers.

This is simulated as an exogenous rise in the REA LTV ratio of impatient households

and entrepreneurs (V J and V HE in equations 22 and 31, respectively). In the initial period, the

LTV ratios in the REA increase by 1 percentage point and subsequently gradually return to their

steady-state values (the persistence of the shock process is set to 0.90).

Figure 2a shows the impact on bank related variables of the increase in the REA LTV ratio.

Although this can be thought as a change in the policy that banks follow to extend their loans,

it is akin to a shift in the demand schedule for loans, as it is encoded in the collateral constraint.

The change allows REA impatient households and entrepreneurs to demand more loans at any

given level of interest rates, since the LTV ratio has increased. The higher demand results in

more loans being extended domestically at a higher interest rate. To finance the higher amount

of loans, REA banks increase their demand for deposits and interbank borrowing (Home lending

in the interbank market increases), bidding up the respective interest rates, while at the same

time they start to increase their capital holdings, although gradually as it is relatively costly to

deviate from the long-run value for bank capital.

23 In all figures, an increase in the real exchange rate represents a depreciation.

25


As reported in Figure 2b, both impatient households and entrepreneurs increase the demand

for real estate, driving up prices. The increase in the collateral value allows them to further

increase their borrowing.

Figure 2c reports the effects on the main macroeconomic variables. REA GDP increases,

driven by the increase in the domestic demand components. REA exports increase, as they

benefit from the real exchange rate depreciation. REA imports increase as well, following the

surge in Home aggregate demand.

Figure 2d shows that the increase in borrowing capacity stimulates, first and foremost, consumption

of borrowers (both households and entrepreneurs). As the demand components rise,

firms start to increase labour demand, pushing up real wages.

Spillovers to the Home bloc are small. Home banks increase their lending to REA banks

through the cross-country interbank market. The additional lending is financed by raising domestic

deposits, while lending to domestic firms and households and the bank capital do not

greatly change. The Home GDP and CPI inflation essentially stay at their baseline levels. Given

the small impact of the REA LTV shock on the Home economy, the union-wide GDP increases

very modestly and inflation hardly changes. This implies that the EA monetary policy rate

increases only slightly (as reported in Figure 2a).

4.3 Increase in Home banks lending in the interbank market

Figures 3a-3d show the implications of a very persistent increase in the amount of liquidity

supplied by the Home banks in the (cross-country) interbank market. In this scenario, resources

for consumption and investment available in one bloc of the EA (Home) are channeled to the

other bloc (REA), via the interbank market. This is implemented by assuming that the long-run

target of Home banks interbank lending, equal to zero in the steady state, increases on impact

to 20 percentage points of steady-state GDP (see equation 4). The shock is temporary but very

persistent, with an AR(1) coefficient equal to 0.995.

Figure3a reportsthat the effects on bank variables. The interest ratein the interbank market

is not greatly affected, as the increased supply of funds is immediately matched by increased

demand. To finance the additional interbank loans, Home banks shift resources away from loans

to domestic households and firms and, at the same time, increase demand for domestic deposits

and, gradually, capital. In the other bloc, REA banks have now access to more resources and

can increase their supply of domestic loans, inducing a fall in the interest rate on loans. They

also correspondingly decrease their recourse to other sources of financing, such as deposits and

bank capital.

Figure 3b shows the effects on borrowing and real estate of this resources reallocation across

countries. Given the higher amount of loans to households and entrepreneurs, demand for real

estate increases in the REA, inducing a surge in the REA real estate prices, which allows for

more borrowing against the same housing stock, and thus amplifies the expansionary impact of

the shock. The opposite happens in the Home country.

26


Similar cross-country asymmetric dynamics characterize the Home and REA macroeconomic

aggregates (see Figures 3c-3d). The increase in REA loans favors REA aggregate demand,

implying an increase in REA labor and driving up inflation in the REA region. To the opposite,

the same variables decrease in the Home bloc.

4.4 Increase in the bank capital requirement

Figures 4a-4d report the responses to an unexpected permanent increase in the capital requirement

implemented simultaneously in the two EA regions. The capital requirement Υ K (see

equation 6) is exogenously increased by 1 percentage point.

Figure 4a reports the responses of the main variables related to the banking sector. They are

broadly similar across the two regions. Specifically, after the shock banks are under-capitalized

with respect to the new level of regulatory requirement. Given the presence of adjustment cost

on capital, banks increase the latter in a gradual manner to limit the tightening of loan supply.

Loans to households and entrepreneurs are cut in a rather moderate way, cushioning almost

all the shock on impact, while the corresponding interest rates are slightly bid up. As loans

contract, there is a shrinkage in banks balance sheet that is matched on the funding side by a

corresponding decrease in deposits demand by banks. The corresponding interest rate declines,

albeit only modestly. Given the limited impact of the shock on economic activity and inflation,

monetary policy is broadly unchanged.

We observe a modest flow of funds in the interbank market towards the Home country, which

become a net borrower, and a sharp increase in the interest rate. The additional loans from the

interbank market allow the Home bank to limit the shrinkage of its balance sheet.

Figure 4b shows the implication of the shock for the real estate. The fall in loans implies

a reduction in real estate prices and an increase in patient households real estate holdings. As

reported in Figure 4c, aggregate consumption and investment and, thus, GDP decrease; CPI

inflation slightly falls as well.

Finally, Figure 4d shows that the lower aggregate demand implies a reduction in the demand

for labour by firms, a fall in employment and real wages and a cut in labor income (which further

depresses consumption).

Overall, the shock has rather mild recessionary (and similar) effects across countries. One

important caveat applies to our results. As simulations are run under perfect foresight, we

are not able to capture possible expansionary effects associated with the reduction in systemic

risk, explained by the increase in bank capital. The expansionary effects can, at least partially,

compensate the recessionary effect of lower loans. From this perspective, our results should be

seen as an upper bound of the negative (and relatively small) effects of the increase in capital

requirement on economic activity.

27


4.5 Sensitivity analysis

We show results obtained under alternative values of the households’ and entrepreneurs’ LTV

ratios and the adjustment costs on the excess bank capital. 24

Specifically, to further emphasize the role of financial frictions and the banking sector for the

transmission mechanism of the shocks, we initially simulate an expansionary monetary policy

shock (-25 annualized b.p.) when in both Home and REA regions the LTV ratios of households

and entrepreneurs, V J and V HE are set to 0.5 instead of 0.7 as in the benchmark calibration.

Second, the increase in the capital requirement is simulated under a larger value of the bank

capital adjustment cost in both Home and REA regions, set to 0.002 instead of 0.001.

Figure 5 reports the results for the monetary policy shock with a lower LTV ratio. Results

do not qualitatively change but they do change quantitatively. GDP increases to a lower extent

in correspondence of the smaller LTV ratio. Given the relatively low LTV ratio, households and

firms can borrow to a lower extent for a given increase in the real estate price. Thus, households

and firms increase their aggregate demand for consumption and investment in a more contained

way. The expansionary effects of the monetary policy easing are less amplified.

Figure 6 reports the results for the increase in the capital requirement with a larger bank

capital adjustment cost. Similarly to the previous case, results do not change qualitatively but

they do change quantitatively. Larger adjustment costs on bank capital can be thought as a

proxy for increased difficulties faced by banks in raising their capital. They imply that banks

have to cut relatively more their loans to achieve the new capital target. Thus, borrowers reduce

relatively more their aggregate demand. The GDP decreases to a larger extent than in the

benchmark case.

Overall, the two simulations, that aim to be illustrative and do not pretend to replicate

empirical evidence, suggest the financial frictions and banking sector can be both sources and

amplification links of financial and nonfinancial shocks in a rather nontrivial way. Thus, the

sensitivity analysis further supports the relevance of the two features for a proper assessment

of policy measures aiming at stabilizing the economy or at permanently changing its structural

aspects.

5 Conclusions

The recent financial crisis and the ensuing prolonged recessionary phase have put new emphasis

on financial shocks and the role of banking and financial features, namely for the transmission

of monetary policy. This paper has outlined the EAGLE-FLI model, aimed at analyzing these

issues in a monetary union setting.

We have built EAGLE-FLI by including the following features in the original EAGLE model:

a microfounded banking sector in each of the four regions of the model; multiple agents in each

24 For similar exercises, see Pataracchia et al. (2013) and Kollmann, Enders and Muller (2011).

28


countries; an enriched financial structure, allowing not only for riskless bonds, but also for banking

loans, deposits, and capital; and related, the cross-country financial structure comprehensive

not only of riskless bonds, but also of a EA interbank market. The model is perturbed by various

financial shocks (LTV ratio, amount of resources that banks lend in the interbank market in the

long run, banks’ capital requirement) that are crucial to assess the interaction between the real

and financial sectors of the economy.

Overall, the large scale of the EAGLE-FLI model, jointly with its microfoundations, allows

to properly analyze the macroeconomic implications of financial factors in the EA countries.

Equivalently, EAGLE-FLI allows to conduct a quantitative analysis in a theoretically coherent

and fully consistent model setup, clearly spelling out all the policy implications. The model

simulations have highlighted the importance of financial variables as sources of the business

cycle and also in the transmission of shocks. Nevertheless, the model can be improved along

several dimensions, that can be crucial for further understanding the transmission of spillovers

in the EA. For example, the financial structure can be further enriched by allowing for bonds

having different maturities. Borrowing constraints can be made occasionally binding. Finally,

and related, uncertainty and risk can be added by appropriately changing the solution algorithm.

These issues and their policy implications constitute an exciting research agenda.

29


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31


Table 1: Steady-State Financial Accounts (Ratio to annual GDP, %)

Home REA US RW

Loans 122 119 148 146

Loans to households 64 61 90 76

Loans to entrepreneurs 58 58 58 70

Interbank 0.0 0.0 n.a. n.a.

Deposits 112 109 137 134

Excess bank capital 0.0 0.0 0.0 0.0

Note: REA=Rest of Euro Area; US=United States; RW=Rest of World

Table 2: Steady-State National Accounts (Ratio to GDP, %)

Home REA US RW

Domestic demand

Private consumption 64 62 66 61

Cons. patient households 29 25 36 36

Cons. impatient households 30 32 25 19

Private investment 17 17 17 21

Public consumption 20 20 16 18

Trade

Imports (total) 38 26 15 11

Imports of consumption goods 26 19 11 6

Imports of investment goods 12 8 4 5

Net foreign assets (ratio to annual GDP) 23 -24 -18 13

Production

Tradables 39 40 37 40

Nontradables 61 60 63 60

Labor 39 39 51 46

Share of World GDP 6 13 19 61

Note: REA=Rest of Euro Area; US=United States; RW=Rest of World

32


Table 3: Financial and Banks Parameters

Home REA US RW

Households LTV ratio (V J ) 0.7 0.7 0.7 0.7

Entrepreneurs LTV ratio (V HE ) 0.7 0.7 0.7 0.7

Entrepreneurs LTV ratio (V KE ) 0.3 0.3 0.3 0.3

Households Loans smoothing (ρ BJ ) 0.4 0.4 0.4 0.4

Entrepreneurs loans smoothing (ρ BE ) 0.4 0.4 0.4 0.4

Capital requirement (Υ K ) 0.08 0.08 0.08 0.08

Banks discount factor (β B ) 1.03 −1 4 1.03 −1 4 1.03 −1 4 1.03 −1 4

Banks share in the population (ω B ) 0.10 0.10 0.10 0.10

Adjustment costs

Deposits (γ DH ) 0.0001 0.0001 0.0001 0.0001

Excess bank capital (γ X ) 0.001 0.001 0.001 0.001

Interbank (γ IB ) 0.001 n.a. n.a n.a

Loans - banks (γ L ) 1.5 1.5 1.5 1.5

Loans - impatient hous. (γ BJ ) 1.5 1.5 1.5 1.5

Loans - entrepreneurs (γ BE ) 1.5 1.5 1.5 1.5

Note: REA=Rest of Euro Area; US=United States; RW=Rest of World

33


Table 4: Households, Entrepreneurs and Firms Behavior

Home REA US RW

Share in the population

Patient households (ω I ) 0.30 0.30 0.30 0.30

Impatient households (ω J ) 0.50 0.50 0.50 0.50

Entrepreneurs (ω E ) 0.10 0.10 0.10 0.10

Households and entrepreneurs

Patient hous. discount factor (β I ) 1.03 −1 4 1.03 −1 4 1.03 −1 4 1.03 −1 4

Imp. households discount factor (β J ) 0.96 0.96 0.96 0.96

Entrepreneurs discount factor (β E ) 0.99 0.99 0.99 0.99

Intertemporal elasticity of substitution (σ −1 ) 1.00 1.00 1.00 1.00

Inverse of the Frisch elasticity of labor (ζ) 2.00 2.00 2.00 2.00

Housing services (ι I ,ι J ) 0.10 0.10 0.10 0.10

Habit persistence (κ) 0.70 0.70 0.70 0.70

Capital depreciation rate(δ K ) 0.025 0.025 0.025 0.025

Housing depreciation rate(δ H ) 0.01 0.01 0.01 0.01

Intermediate-good firms (trad. and nontrad. sectors)

Substitution btw. labor and capital 1.00 1.00 1.00 1.00

Bias towards capital - tradables (α T ) 0.30 0.30 0.30 0.30

Bias towards housing - tradables (α HT ) 0.01 0.01 0.01 0.01

Bias towards capital - nontradables (α N ) 0.37 0.40 0.31 0.43

Bias towards housing - nontradables (α HN ) 0.01 0.01 0.01 0.01

Substitution btw. I-type and J-type labor (η) 4.33 4.33 7.25 7.25

Final consumption-good firms

Substitution btw. domestic and imported trad. goods (µ TC ) 2.50 2.50 2.50 2.50

Bias towards domestic tradables goods (v TC ) 0.04 0.36 0.50 0.69

Substitution btw. tradables and nontradables (µ C ) 0.50 0.50 0.50 0.50

Bias towards tradable goods (v C ) 0.45 0.45 0.35 0.35

Substitution btw. consumption good imports (µ IMC ) 2.50 2.50 2.50 2.50

Final investment-good firms

Substitution btw. domestic and imported trad. goods (µ TI ) 2.50 2.50 2.50 2.50

Bias towards domestic tradables goods (v TI ) 0.03 0.48 0.66 0.67

Substitution btw. tradables and nontradables (µ I ) 0.50 0.50 0.50 0.50

Bias towards tradable goods (v I ) 0.75 0.75 0.75 0.75

Substitution btw. investment good imports (µ IMI ) 2.50 2.50 2.50 2.50

Note: REA=Rest of Euro Area; US=United States; RW=Rest of World

34


Table 5: Price and Wage Markups (Implied Elasticities of Substitution)

Tradables (θ T ) Nontradables (θ N ) Wages (η I = η J )

Home 1.20 (6.0) 1.50 (3.0) 1.30 (4.3)

REA 1.20 (6.0) 1.50 (3.0) 1.30 (4.3)

US 1.20 (6.0) 1.28 (4.6) 1.16 (7.3)

RW 1.20 (6.0) 1.28 (4.6) 1.16 (7.3)

Note: REA=Rest of Euro Area; US=United States; RW=Rest of World

Table 6: Real and Nominal Rigidities

Home REA US RW

Adjustment costs

Imports of consumption goods (γ IM C) 2.00 2.00 2.00 2.00

Imports of investment goods (γ IM I) 1.00 1.00 1.00 1.00

Capital utilization (γ u2 ) 2000 2000 2000 2000

Investment (γ I ) 6.00 6.00 4.00 4.00

Intermediation cost function - USD bond (γ B ∗) 0.01 0.01 ... 0.01

Intermediation cost function - Euro bond (γ B EA) ... 0.01 ... ...

Calvo parameters

Wages - households I and J (ξ I and ξ J ) 0.75 0.75 0.75 0.75

Prices - domestic tradables (ξ H ) and nontradables (ξ N ) 0.92 0.92 0.75 0.75

Prices - exports (ξ X ) 0.75 0.75 0.75 0.75

Degree of indexation

Wages - households I and J (χ I and χ J ) 0.75 0.75 0.75 0.75

Prices - domestic tradables (χ H ) and nontradables (χ N ) 0.50 0.50 0.50 0.50

Prices - exports (χ X ) 0.50 0.50 0.50 0.50

Note: REA=Rest of Euro Area; US=United States; RW=Rest of World

35


Table 7: International Linkages (Trade Matrix, Share of Domestic GDP, %)

Home REA US RW

Consumption-good imports

Substitution btw. consumption good imports (µ IMC ) 2.50 2.50 2.50 2.50

Total consumption good imports 25.7 18.7 11.0 6.1

From partner

Home - 4.0 0.4 1.3

REA 10.2 - 0.9 2.7

US 1.3 1.3 - 2.2

RW 14.3 13.5 9.7 -

Investment-good imports

Substitution btw. investment good imports (µ IMI ) 2.50 2.50 2.50 2.50

Total investment good imports 12.0 7.7 4.2 4.5

From partner

Home - 1.9 0.2 1.1

REA 4.1 - 0.3 1.3

US 1.3 1.2 - 2.1

RW 6.7 4.6 3.6 -

Note: REA=Rest of Euro Area; US=United States; RW=Rest of World

36


Table 8: Monetary and Fiscal Policy

Home REA US RW

Monetary authority

Inflation target (Π 4 ) 1.02 1.02 1.02 1.02

Interest rate inertia (φ R ) 0.87 0.87 0.87 0.87

Interest rate sensitivity to inflation gap (φ Π ) 1.70 1.70 1.70 1.70

Interest rate sensitivity to output growth (φ Y ) 0.10 0.10 0.10 0.10

Fiscal authority

Government debt-to-output ratio (B Y ) 2.40 2.40 2.40 2.40

Sensitivity of lump-sum taxes to debt-to-output ratio (φ BY ) 5.00 5.00 5.00 5.00

Consumption tax rate (τ C ) 0.183 0.183 0.077 0.077

Dividend tax rate (τ D ) 0.00 0.00 0.00 0.00

Capital income tax rate (τ K ) 0.19 0.19 0.16 0.16

Labor income tax rate (τ N ) 0.122 0.122 0.154 0.154

Rate of social security contribution by firms (τ Wf ) 0.219 0.219 0.071 0.071

Rate of social security contribution by households (τ Wh ) 0.118 0.118 0.071 0.071

Note: REA=Rest of Euro Area; US=United States; RW=Rest of World

37


Figure 1a. Reduction in the EA interest rate – Effects on bank variables

0.1

Monetary policy rate

0.1

Loans Interest rate

0

0

Home

REA

−0.1

−0.1

−0.2

−0.2

−0.3

5 10 15 20 25 30 35 40

−0.3

5 10 15 20 25 30 35 40

0.1

Deposits interest rate

0.05

Interbank interest rate

0

Home

REA

0

−0.05

−0.1

−0.1

−0.2

−0.15

−0.3

5 10 15 20 25 30 35 40

−0.2

5 10 15 20 25 30 35 40

2

Households deposits

0

Home interbank lending

1.5

Home

REA

−0.01

1

−0.02

0.5

−0.03

0

−0.04

−0.5

5 10 15 20 25 30 35 40

−0.05

5 10 15 20 25 30 35 40

0.05

Bank capital

1.5

Loans

0

Home

REA

1

Home

REA

−0.05

0.5

−0.1

−0.15

0

−0.2

−0.5

5 10 15 20 25 30 35 40

5 10 15 20 25 30 35 40

Horizontal axis: quarters. Vertical axis: % deviations from the baseline, except for interest rates (annualized

percentage-pointdeviations) andtheinterbankposition-to-GDP ratio(percentage-point deviations).

38


1

0.5

Figure 1b. Reduction in the EA interest rate – Effects on borrowing and housing

Impatient households borrowing

Home

REA

2.5

2

1.5

Entrepreneurs borrowing

Home

REA

1

0

0.5

0

−0.5

5 10 15 20 25 30 35 40

−0.5

5 10 15 20 25 30 35 40

0.6

0.4

Impatient households housing

Home

REA

15

10

Entrepreneurs housing

Home

REA

0.2

5

0

0

−0.2

5 10 15 20 25 30 35 40

−5

5 10 15 20 25 30 35 40

15

10

Tradable sector housing

Home

REA

15

10

Nontradable sector housing

Home

REA

5

5

0

0

−5

5 10 15 20 25 30 35 40

−5

5 10 15 20 25 30 35 40

1

0

Patient households housing

Home

REA

0.8

0.6

Housing price

Home

REA

−1

0.4

−2

0.2

−3

0

−4

−0.2

5 10 15 20 25 30 35 40

5 10 15 20 25 30 35 40

Horizontal axis: quarters. Vertical axis: % deviations from the baseline.

39


Figure 1c. Reduction in the EA interest rate – Effects on main macro variables

0.5

GDP

0.5

Aggregate consumption

0.4

Home

REA

0.4

Home

REA

0.3

0.3

0.2

0.2

0.1

0.1

0

5 10 15 20 25 30 35 40

0

5 10 15 20 25 30 35 40

1.5

Investment

0.4

Export

1

Home

REA

0.3

Home

REA

0.5

0.2

0

0.1

−0.5

5 10 15 20 25 30 35 40

0

5 10 15 20 25 30 35 40

0.6

Import

0.4

Real exch. rate

0.4

Home

REA

0.3

Home

REA

0.2

0.2

0

0.1

−0.2

5 10 15 20 25 30 35 40

0

5 10 15 20 25 30 35 40

0.15

CPI inflation

0.4

EA GDP

0.1

Home

REA

0.3

0.05

0.2

0

0.1

−0.05

0

5 10 15 20 25 30 35 40

5 10 15 20 25 30 35 40

Horizontal axis: quarters. Vertical axis: % deviations from the baseline, except for inflation (annualized

percentage-point deviations). GDP and its components are reported in real terms.

40


0.25

0.2

0.15

0.1

0.05

Figure 1d. Reduction in the EA interest rate – Effects on consumption and labor

Patient hous. consumption

Home

REA

0.6

0.4

0.2

0

Impatient households consumption

Home

REA

0

5 10 15 20 25 30 35 40

−0.2

5 10 15 20 25 30 35 40

1.5

1

Entrepreneurs consumption

Home

REA

0.6

0.4

Patient hous. labor

Home

REA

0.2

0.5

0

0

5 10 15 20 25 30 35 40

−0.2

5 10 15 20 25 30 35 40

0.4

0.3

Impatient hous. labor

Home

REA

0.6

0.4

Labor

Home

REA

0.2

0.1

0.2

0

0

−0.1

5 10 15 20 25 30 35 40

−0.2

5 10 15 20 25 30 35 40

0.12

0.1

0.08

Pat. hous. real wage

Home

REA

0.12

0.1

0.08

Imp. hous. real wage

Home

REA

0.06

0.06

0.04

0.04

0.02

0.02

0

0

5 10 15 20 25 30 35 40

5 10 15 20 25 30 35 40

Horizontal axis: quarters. Vertical axis: % deviations from the baseline.

41


Figure 2a. Increase in REA LTV ratio – Effects on bank variables

0.02

Monetary policy rate

0.08

Loans Interest rate

0.01

0.06

Home

REA

0.04

0

0.02

−0.01

0

−0.02

5 10 15 20 25 30 35 40

−0.02

5 10 15 20 25 30 35 40

0.06

Deposits interest rate

0.15

Interbank interest rate

0.04

Home

REA

0.1

0.02

0.05

0

0

−0.02

5 10 15 20 25 30 35 40

−0.05

5 10 15 20 25 30 35 40

2.5

Households deposits

1

Home interbank lending

2

Home

REA

1.5

0.5

1

0.5

0

0

−0.5

5 10 15 20 25 30 35 40

−0.5

5 10 15 20 25 30 35 40

0.4

Bank capital

2

Loans

0.3

Home

REA

1.5

Home

REA

0.2

1

0.1

0

0.5

−0.1

0

5 10 15 20 25 30 35 40

5 10 15 20 25 30 35 40

Horizontal axis: quarters. Vertical axis: % deviations from the baseline, except for interest rates (annualized

percentage-pointdeviations) andtheinterbankposition-to-GDP ratio(percentage-point deviations).

42


3

2

Figure 2b. Increase in REA LTV ratio – Effects on borrowing and housing

Impatient households borrowing

Home

REA

1.5

1

Entrepreneurs borrowing

Home

REA

1

0.5

0

0

−1

5 10 15 20 25 30 35 40

−0.5

5 10 15 20 25 30 35 40

2

1.5

Impatient households housing

Home

REA

6

4

Entrepreneurs housing

Home

REA

1

0.5

2

0

0

−0.5

5 10 15 20 25 30 35 40

−2

5 10 15 20 25 30 35 40

6

4

Tradable sector housing

Home

REA

6

4

Nontradable sector housing

Home

REA

2

2

0

0

−2

5 10 15 20 25 30 35 40

−2

5 10 15 20 25 30 35 40

1

0

−1

−2

−3

Patient households housing

Home

REA

0.5

0.4

0.3

0.2

Housing price

Home

REA

−4

0.1

−5

0

5 10 15 20 25 30 35 40

5 10 15 20 25 30 35 40

Horizontal axis: quarters. Vertical axis: % deviations from the baseline.

43


Figure 2c. Increase in REA LTV ratio – Effects on main macro variables

0.3

0.2

GDP

Home

REA

0.6

0.4

Aggregate consumption

Home

REA

0.1

0.2

0

0

−0.1

5 10 15 20 25 30 35 40

−0.2

5 10 15 20 25 30 35 40

0.4

0.2

Investment

Home

REA

0.15

0.1

Export

Home

REA

0

0.05

0

−0.2

−0.05

−0.4

5 10 15 20 25 30 35 40

−0.1

5 10 15 20 25 30 35 40

0.3

0.2

0.1

0

Import

Home

REA

0.02

0.015

0.01

0.005

0

Real exch. rate

Home

REA

−0.1

−0.005

−0.2

5 10 15 20 25 30 35 40

−0.01

5 10 15 20 25 30 35 40

5 x 10−3 CPI inflation

0

Home

REA

0.15

0.1

EA GDP

−5

0.05

−10

0

−15

−0.05

5 10 15 20 25 30 35 40

5 10 15 20 25 30 35 40

Horizontal axis: quarters. Vertical axis: % deviations from the baseline, except for inflation (annualized

percentage-point deviations). GDP and its components are reported in real terms.

44


Figure 2d. Increase in REA LTV ratio – Effects on consumption and labor

0.08

Patient hous. consumption

0.6

Impatient households consumption

0.06

Home

REA

0.4

Home

REA

0.2

0.04

0

0.02

−0.2

0

5 10 15 20 25 30 35 40

−0.4

5 10 15 20 25 30 35 40

0.6

Entrepreneurs consumption

0.3

Patient hous. labor

0.4

Home

REA

0.2

Home

REA

0.1

0.2

0

0

−0.1

−0.2

5 10 15 20 25 30 35 40

−0.2

5 10 15 20 25 30 35 40

0.2

Impatient hous. labor

0.2

Labor

0.15

Home

REA

0.15

Home

REA

0.1

0.1

0.05

0.05

0

0

−0.05

5 10 15 20 25 30 35 40

−0.05

5 10 15 20 25 30 35 40

0.02

Pat. hous. real wage

0.04

Imp. hous. real wage

0.01

Home

REA

0.02

Home

REA

0

0

−0.01

−0.02

−0.02

−0.04

−0.03

−0.06

5 10 15 20 25 30 35 40

5 10 15 20 25 30 35 40

Horizontal axis: quarters. Vertical axis: % deviations from the baseline.

45


Figure 3a. Increase in Home long-run interbank position – Effects on bank variables

0.04

Monetary policy rate

0.15

Loans Interest rate

0.03

0.1

Home

REA

0.02

0.05

0.01

0

0

5 10 15 20 25 30 35 40

−0.05

5 10 15 20 25 30 35 40

0.15

Deposits interest rate

0

Interbank interest rate

0.1

Home

REA

−0.005

−0.01

0.05

−0.015

0

−0.02

−0.025

−0.05

5 10 15 20 25 30 35 40

−0.03

5 10 15 20 25 30 35 40

4

Households deposits

20

Home interbank lending

3

2

Home

REA

15

1

10

0

−1

5

−2

5 10 15 20 25 30 35 40

0

5 10 15 20 25 30 35 40

0.2

Bank capital

1

Loans

0.1

Home

REA

0.5

Home

REA

0

0

−0.1

−0.2

−0.5

−0.3

−1

5 10 15 20 25 30 35 40

5 10 15 20 25 30 35 40

Horizontal axis: quarters. Vertical axis: % deviations from the baseline, except for interest rates (annualized

percentage-pointdeviations) andtheinterbankposition-to-GDP ratio(percentage-point deviations).

46


Figure 3b. Increase in Home long-run interbank position – Effects on borrowing and housing

1

0.5

0

Impatient households borrowing

Home

REA

1

0.5

Entrepreneurs borrowing

Home

REA

−0.5

0

−1

5 10 15 20 25 30 35 40

−0.5

5 10 15 20 25 30 35 40

0.4

0.2

Impatient households housing

Home

REA

6

4

Entrepreneurs housing

Home

REA

0

2

−0.2

0

−0.4

−2

−0.6

5 10 15 20 25 30 35 40

−4

5 10 15 20 25 30 35 40

6

4

Tradable sector housing

Home

REA

6

4

Nontradable sector housing

Home

REA

2

2

0

0

−2

−2

−4

5 10 15 20 25 30 35 40

−4

5 10 15 20 25 30 35 40

2

1

Patient households housing

Home

REA

0.4

0.2

Housing price

Home

REA

0

0

−0.2

−1

−0.4

−2

−0.6

5 10 15 20 25 30 35 40

5 10 15 20 25 30 35 40

Horizontal axis: quarters. Vertical axis: % deviations from the baseline.

47


Figure 3c. Increase in Home long-run interbank position – Effects on main macro variables

0.15

GDP

0.3

Aggregate consumption

0.1

Home

REA

0.2

Home

REA

0.05

0.1

0

0

−0.05

−0.1

−0.1

5 10 15 20 25 30 35 40

−0.2

5 10 15 20 25 30 35 40

0.6

Investment

0.3

Export

0.4

Home

REA

0.2

Home

REA

0.2

0.1

0

−0.2

0

−0.4

5 10 15 20 25 30 35 40

−0.1

5 10 15 20 25 30 35 40

0.4

Import

0.06

Real exch. rate

0.2

Home

REA

0.04

Home

REA

0.02

0

0

−0.2

−0.02

−0.4

5 10 15 20 25 30 35 40

−0.04

5 10 15 20 25 30 35 40

0.04

CPI inflation

0.08

EA GDP

0.03

Home

REA

0.06

0.02

0.04

0.01

0.02

0

0

5 10 15 20 25 30 35 40

5 10 15 20 25 30 35 40

Horizontal axis: quarters. Vertical axis: % deviations from the baseline, except for inflation (annualized

percentage-point deviations). GDP and its components are reported in real terms.

48


Figure 3d. Increase in Home long-run interbank position – Effects on consumption and labor

0.2

Patient hous. consumption

0.4

Impatient households consumption

0.1

Home

REA

0.2

Home

REA

0

0

−0.1

−0.2

−0.2

5 10 15 20 25 30 35 40

−0.4

5 10 15 20 25 30 35 40

0.6

Entrepreneurs consumption

0.15

Patient hous. labor

0.4

Home

REA

0.1

Home

REA

0.2

0.05

0

−0.2

0

−0.4

5 10 15 20 25 30 35 40

−0.05

5 10 15 20 25 30 35 40

0.15

Impatient hous. labor

0.15

Labor

0.1

Home

REA

0.1

Home

REA

0.05

0.05

0

0

−0.05

5 10 15 20 25 30 35 40

−0.05

5 10 15 20 25 30 35 40

0.06

Pat. hous. real wage

0.05

Imp. hous. real wage

0.04

Home

REA

Home

REA

0.02

0

0

−0.02

−0.04

−0.06

−0.05

5 10 15 20 25 30 35 40

5 10 15 20 25 30 35 40

Horizontal axis: quarters. Vertical axis: % deviations from the baseline.

49


Figure 4a. Increase in EA bank capital requirement – Effects on bank variables

0

Monetary policy rate

0.04

Loans Interest rate

−0.005

0.03

Home

REA

0.02

−0.01

0.01

−0.015

5 10 15 20 25 30 35 40

0

5 10 15 20 25 30 35 40

0

Deposits interest rate

0.8

Interbank interest rate

−0.005

Home

REA

0.6

−0.01

0.4

−0.015

0.2

−0.02

5 10 15 20 25 30 35 40

0

5 10 15 20 25 30 35 40

0

Households deposits

0

Home interbank lending

−0.2

Home

REA

−0.2

−0.4

−0.4

−0.6

−0.6

−0.8

5 10 15 20 25 30 35 40

−0.8

5 10 15 20 25 30 35 40

5

Bank capital

0

Loans

4

3

Home

REA

−0.1

Home

REA

2

−0.2

1

0

−0.3

−1

−0.4

5 10 15 20 25 30 35 40

5 10 15 20 25 30 35 40

Horizontal axis: quarters. Vertical axis: % deviations from the baseline, except for interest rates (annualized

percentage-pointdeviations) andtheinterbankposition-to-GDP ratio(percentage-point deviations).

50


Figure 4b. Increase in EA bank capital requirement – Effects on borrowing and housing

0

Impatient households borrowing

0

Entrepreneurs borrowing

−0.1

Home

REA

−0.1

Home

REA

−0.2

−0.2

−0.3

−0.3

−0.4

5 10 15 20 25 30 35 40

−0.4

5 10 15 20 25 30 35 40

0

Impatient households housing

0.5

Entrepreneurs housing

−0.05

Home

REA

0

Home

REA

−0.1

−0.15

−0.5

−1

−1.5

−0.2

−2

−0.25

5 10 15 20 25 30 35 40

−2.5

5 10 15 20 25 30 35 40

0.5

Tradable sector housing

0.5

Nontradable sector housing

0

Home

REA

0

Home

REA

−0.5

−0.5

−1

−1

−1.5

−1.5

−2

−2

−2.5

5 10 15 20 25 30 35 40

−2.5

5 10 15 20 25 30 35 40

1

Patient households housing

0

Housing price

0.8

Home

REA

−0.05

Home

REA

0.6

−0.1

0.4

0.2

−0.15

0

−0.2

5 10 15 20 25 30 35 40

5 10 15 20 25 30 35 40

Horizontal axis: quarters. Vertical axis: % deviations from the baseline.

51


Figure 4c. Increase in EA bank capital requirement – Effects on main macro variables

0

GDP

0

Aggregate consumption

−0.02

Home

REA

−0.02

Home

REA

−0.04

−0.04

−0.06

−0.06

−0.08

5 10 15 20 25 30 35 40

−0.08

5 10 15 20 25 30 35 40

0

Investment

0.01

Export

−0.05

Home

REA

0

Home

REA

−0.1

−0.15

−0.01

−0.02

−0.03

−0.2

−0.04

−0.25

5 10 15 20 25 30 35 40

−0.05

5 10 15 20 25 30 35 40

0

Import

0

Real exch. rate

−0.02

Home

REA

Home

REA

−0.04

−0.005

−0.06

−0.08

−0.01

−0.1

−0.12

5 10 15 20 25 30 35 40

−0.015

5 10 15 20 25 30 35 40

0

CPI inflation

0

EA GDP

Home

REA

−0.01

−0.005

−0.02

−0.03

−0.01

−0.04

−0.05

−0.015

−0.06

5 10 15 20 25 30 35 40

5 10 15 20 25 30 35 40

Horizontal axis: quarters. Vertical axis: % deviations from the baseline, except for inflation (annualized

percentage-point deviations). GDP and its components are reported in real terms.

52


Figure 4d. Increase in EA bank capital requirement – Effects on consumption and labor

0

Patient hous. consumption

0

Impatient households consumption

−0.01

Home

REA

−0.02

−0.04

Home

REA

−0.02

−0.06

−0.03

−0.08

−0.1

−0.04

5 10 15 20 25 30 35 40

−0.12

5 10 15 20 25 30 35 40

0

Entrepreneurs consumption

0.02

Patient hous. labor

−0.05

Home

REA

0

Home

REA

−0.1

−0.02

−0.15

−0.04

−0.2

−0.06

−0.25

5 10 15 20 25 30 35 40

−0.08

5 10 15 20 25 30 35 40

0.02

Impatient hous. labor

0.02

Labor

0

Home

REA

0

Home

REA

−0.02

−0.02

−0.04

−0.04

−0.06

−0.06

5 10 15 20 25 30 35 40

−0.08

5 10 15 20 25 30 35 40

0

Pat. hous. real wage

0

Imp. hous. real wage

−0.005

Home

REA

−0.005

Home

REA

−0.01

−0.01

−0.015

−0.015

−0.02

−0.02

−0.025

−0.025

−0.03

−0.03

5 10 15 20 25 30 35 40

5 10 15 20 25 30 35 40

Horizontal axis: quarters. Vertical axis: % deviations from the baseline.

53


Figure 5. Sensitivity. Low LTV ratio

0.5

Home GDP

0.4

REA GDP

0.4

Benchmark

Low LTV ratio

0.3

Benchmark

Low LTV ratio

0.3

0.2

0.2

0.1

0.1

0

5 10 15 20 25 30 35 40

0

5 10 15 20 25 30 35 40

0.15

Home CPI inflation

0.15

REA CPI inflation

0.1

Benchmark

Low LTV ratio

0.1

Benchmark

Low LTV ratio

0.05

0.05

0

0

−0.05

5 10 15 20 25 30 35 40

−0.05

5 10 15 20 25 30 35 40

1

Home Impatient households borrowing

0.8

REA Impatient households borrowing

Benchmark

Low LTV ratio

0.6

Benchmark

Low LTV ratio

0.5

0.4

0

0.2

0

−0.5

5 10 15 20 25 30 35 40

−0.2

5 10 15 20 25 30 35 40

2.5

Home Entrepreneurs borrowing

2

REA Entrepreneurs borrowing

2

Benchmark

Low LTV ratio

1.5

Benchmark

Low LTV ratio

1.5

1

0.5

1

0.5

0

0

−0.5

−0.5

5 10 15 20 25 30 35 40

5 10 15 20 25 30 35 40

Horizontal axis: quarters. Vertical axis: % deviations from the baseline. Benchmark: LTV ratio=0.7;

Low LTV ratio: LTV ratio=0.5.

54


Figure 6. Sensitivity. High adj. cost on bank capital γ X

0

Home GDP

0

REA GDP

−0.02

Benchmark

High adj. cost

−0.02

Benchmark

High adj. cost

−0.04

−0.06

−0.08

−0.04

−0.06

−0.1

−0.08

−0.12

5 10 15 20 25 30 35 40

−0.1

5 10 15 20 25 30 35 40

0

Home CPI inflation

0

REA CPI inflation

−0.005

Benchmark

High adj. cost

−0.005

Benchmark

High adj. cost

−0.01

−0.01

−0.015

−0.015

−0.02

−0.02

−0.025

5 10 15 20 25 30 35 40

−0.025

5 10 15 20 25 30 35 40

0

Home Impatient households borrowing

0

REA Impatient households borrowing

−0.1

Benchmark

High adj. cost

−0.1

Benchmark

High adj. cost

−0.2

−0.2

−0.3

−0.3

−0.4

−0.4

−0.5

5 10 15 20 25 30 35 40

−0.5

5 10 15 20 25 30 35 40

0

Home Entrepreneurs borrowing

0

REA Entrepreneurs borrowing

−0.2

Benchmark

High adj. cost

−0.2

Benchmark

High adj. cost

−0.4

−0.4

−0.6

−0.6

−0.8

−0.8

5 10 15 20 25 30 35 40

5 10 15 20 25 30 35 40

Horizontal axis: quarters. Vertical axis: % deviations from the baseline. Benchmark: adj.cost=0.001;

High adj. cost: adj. cost=0.002.

55


Technical Appendix: Equations

Below we state the new equations (compared to the standard version of the EAGLE model),

written in real terms. The price of consumption is the numeraire.

Banks first order conditions (FOC), budget constraint and capital requirement

• FOC Marginal utility of dividends

Λ B,t = ( div B t

) −σ

(62)

• FOC deposits supply

• FOC loans supply

[

R D ]

t

Λ B,t = β B E t Λ B,t+1 −Λ B,t γ X (x t − ¯x) (63)

Π C,t+1

[

R L ] (

t lt

Λ B,t = β B E t Λ B,t+1 −γ L Λ B,t

Π C,t+1

+β B γ L E t

[

Λ B,t+1

(

lt+1

l t

−1

)

lt+1

l 2 t

) 1

−1

l t−1

]

l t−1

−Λ B,t γ X (1−Υ K,t )(x t − ¯x) (64)

• FOC interbank loans

[

R IB ]

t

Λ B,t = β B E t Λ B,t+1

Π C,t+1

• budget constraint

−Λ B,t γ IB (l IB

t − κIB p Y Y

ω B

)−Λ B,t γ X (x t − ¯x) (65)

div B t

= −l t + RL t−1

Π C,t

l t−1 −l IB

t + RIB t−1

t−1

Π C,t

l IB

+d Supply

t

− RD t−1

Π C,t

d Supply

t−1 −Γ L,t −Γ IB,t −Γ X,t (66)

• capital requirement: excess bank capital definition

x t ≡ (1−Υ K,t )l t −d Supply

t

+l IB

t (67)

• bank loans adjustment cost

Γ L ≡ γ L

2

( ) 2 lt

1

(68)

l t−1

56


• bank capital adjustment cost

Γ X ≡ γ X

2 (x t − ¯x) 2 (69)

• interbank loans adjustment cost

Γ IB ≡ γ IB

2

(

l IB

t − κIB p Y Y

ω B

) 2

(70)

Borrowers FOC, budget constraint and borrowing constraint

• FOC marginal utility of nondurables consumption

( ) −σ CJ,t −κC J,t−1

Λ J,t (1+τ C ) =

(71)

1−κ

• FOC loans demand

[

R L ]

t

Λ J,t = β J E t Λ J,t+1

Π C,t+1

− γ BJ Λ J,t

(

bJ,t

b J,t−1

−1

) [

1

+β J γ BJ E t

b J,t−1

+ Λ JC,t R L t −ρ b J

β J E t

[

Λ JC,t+1

R L t

Π C,t+1

Π

]

Λ J,t+1

(

bJ,t+1

b J,t

−1

)

bJ,t+1

b 2 J,t

]

(72)

• FOC real estate demand

Λ J,t qt H = ι J [

+β J E t ΛJ,t+1 (1−δ H )q H ] [ ]

t+1 +(1−ρBJ )Λ JC,t V J,t E t q

H

H t+1 Π C,t+1

J,t

(73)

• budget constraint

b J,t − RL t−1

Π C,t

b J,t−1 = (1−τ N −τ WH )w J,t N J,t + tr J

ω J

− (1+τ C )C J,t −q H t (H J,t −(1−δ H )H J,t−1 )−Γ BJ,t (74)

• borrowing constraint

−b J,t R L t ≤ −ρ B J

Πb J,t−1

R L t−1

Π C,t

+(1−ρ BJ )V J,t E t

[

q

H

t+1 Π C,t+1 H J,t

]

(75)

• adjustment cost on borrowing position

Γ BJ,t ≡ γ B J

2

( ) 2 bJ,t

−1

(76)

b J,t−1

57


Entrepreneurs FOC, budget constraint, borrowing constraint

• FOC marginal utility of nondurables consumption

• FOC real estate demand

( ) −σ CE,t −κC E,t−1

Λ E,t (1+τ C,t ) =

(77)

1−κ

Λ E,t qt H [

= β E E t ΛE,t+1 r H,t+1 +Λ E,t+1 (1−δ H )qt+1

H ] [ ]

+(1−ρBE )Λ EC,t V HE,tE t q

H

t+1 Π C,t+1

(78)

• FOC loans demand

[

R L ]

t

Λ E,t = β E E t Λ E,t+1

Π C,t+1

( ) [ (

bE,t 1

bE,t+1

− γ L Λ E,t −1 +β E γ BE E t Λ E,t+1 −1

b E,t−1 b E,t−1 b E,t

[

+ Λ EC,t Rt L R L ]

t

−β E ρ BE ΠE t Λ EC,t+1

Π C,t+1

• FOC investment in physical capital

)

bE,t+1

b 2 E,t

]

(79)

p I t

= q K t

(

1−ΓI,t −Γ ′ I,tI E,t

)

[

]

Λ E,t+1

+β E E t q K I

t+1

Λ Γ′ E,t+1

2

I,t+1

E,t I E,t

(80)

• FOC physical capital

Λ E,t q K t = β E E t

[

ΛE,t+1 (1−τ K,t+1 ) ( r K,t+1 u t+1 −Γ u,t+1 p I t+1)]

+τK,t δ K p I t

+ β E E t

[

ΛE,t+1 q K t+1(1−δ K ) ] +(1−ρ BE )Λ EC,t V KE,tE t

[

q

K

t+1 Π C,t+1

]

(81)

• FOC capacity utilisation

• Physical capital accumulation

r K,t = Γ ′ u,t pI t (82)

Γ ′ u = (β−1 E −1+δ K)q K −δ K τ K p I

(1−τ K )p I +γ u2 (u t −1) (83)

K E,t = (1−δ K )K E,t−1 +(1−Γ I,t )I E,t (84)

58


• budget constraint

b E,t − RL t−1

b E,t−1 = r H,t H E,t−1 +(1−τ K,t ) ( r K,t u t −Γ u,t p I )

t KE,t−1 +τ K,t δ K p I

Π

tK E,t−1

C,t

− q H t (H E,t −(1−δ H )H E,t−1 )−(1+τ C,t )C E,t −p I ti E,t

− Γ BE,t (85)

• borrowing constraint

−R L t b E,t ≤ −ρ BE Πb E,t−1

R L t−1

Π C,t

+(1−ρ BE )V HE,tE t

[

q

H

t+1 H E,t Π C,t+1

]

+(1−ρBE )V K,t E t

[

q

K

t+1 K E,t Π C,t+1

]

• adjustment cost on borrowing position

(86)

Γ BE,t ≡ γ B E

2

( ) 2 bE,t

−1

(87)

b E,t−1

Savers’ FOC

• FOC marginal utility of nondurables consumption

( ) −σ CI,t −κC I,t−1

Λ I,t (1+τ C ) =

(88)

1−κ

• FOC deposits demand

[ (

Λ I,t 1+γ DH d Dem κ D p Y )] [

Y

R D ]

t

t − = β I E t Λ I,t+1

1−ω J −ω E −ω B Π C,t+1

(89)

• FOC real estate demand

Λ I,t qt H = ι I [

+β I E t ΛI,t+1 (1−δ H )q H ]

t+1

H I,t

(90)

Intermediate goods production

• Production functions

Y S,N

t = z N,t

(

K

D

t

) αKN (

H

D

t

) αHN (

N

D

t

) 1−αKN−α HN

(91)

Y S,T

t = z T,t

(

K

D

t

) αKT (

H

D

t

) αHT (

N

D

t

) 1−αKT−α HT

(92)

59


• Input demand functions

r H,t H N,D

t

r H,t H T,D

t

r K,t K N,D

t

r K,t K T,D

t

= α HN Y S,N

t MC N t (93)

= α HT Y S,T

t MC T t (94)

= α KN Y S,N

t MC N t (95)

= α KT Y S,T

t MC T t (96)

Market clearing conditions and net foreign asset position

• Housing market

(1−ω J −ω E −ω B )H I,t +ω J H J,t +ω E H E,t = ¯H; (97)

H T t +H NT

t = ω E H E,t (98)

• Loans market

• Deposits market

ω B d Supply

t

ω B l t +ω J b J,t +ω E b E,t = 0 (99)

= (1−ω J −ω E −ω B )d Dem

t (100)

• EA cross-country interbank market (L IB,REA

t

s H ω H Bl IB,H

t

is in H “real” currency)

+s REA ωB

REA l IB,REA

t = 0 (101)

• Net foreign assets position (in “real” US dollars)

L IB

t

(1−ω J −ω E −ω B )B US,t +ω B

S H,US

t

+(1−ω J −ω E −ω B ) BEA I,t

S H,US

t

(1−ω J −ω E −ω B )B US,t−1 R US

t−1 +ω B

+(1−ω J −ω E −ω B ) BEA I,t−1 R t−1

S H,US

t

=

L IB

t−1 RIB t−1

S H,US

t

+ TBH t

S H,US

t

, (102)

60


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A. MERCATANTI, A likelihood-based analysis for relaxing the exclusion restriction in randomized

experiments with imperfect compliance, Australian and New Zealand Journal of Statistics, v. 55, 2,

pp. 129-153, TD No. 683 (August 2008).

F. CINGANO and P. PINOTTI, Politicians at work. The private returns and social costs of political connections,

Journal of the European Economic Association, v. 11, 2, pp. 433-465, TD No. 709 (May 2009).

F. BUSETTI and J. MARCUCCI, Comparing forecast accuracy: a Monte Carlo investigation, International

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A. FINICELLI, P. PAGANO and M. SBRACIA, Ricardian Selection, Journal of International Economics, v. 89,

1, pp. 96-109, TD No. 728 (October 2009).

L. MONTEFORTE and G. MORETTI, Real-time forecasts of inflation: the role of financial variables, Journal

of Forecasting, v. 32, 1, pp. 51-61, TD No. 767 (July 2010).

R. GIORDANO and P. TOMMASINO, Public-sector efficiency and political culture, FinanzArchiv, v. 69, 3, pp.

289-316, TD No. 786 (January 2011).

E. GAIOTTI, Credit availablility and investment: lessons from the "Great Recession", European Economic

Review, v. 59, pp. 212-227, TD No. 793 (February 2011).

F. NUCCI and M. RIGGI, Performance pay and changes in U.S. labor market dynamics, Journal of

Economic Dynamics and Control, v. 37, 12, pp. 2796-2813, TD No. 800 (March 2011).

G. CAPPELLETTI, G. GUAZZAROTTI and P. TOMMASINO, What determines annuity demand at retirement?,

The Geneva Papers on Risk and Insurance – Issues and Practice, pp. 1-26, TD No. 805 (April 2011).

A. ACCETTURO e L. INFANTE, Skills or Culture? An analysis of the decision to work by immigrant women

in Italy, IZA Journal of Migration, v. 2, 2, pp. 1-21, TD No. 815 (July 2011).

A. DE SOCIO, Squeezing liquidity in a “lemons market” or asking liquidity “on tap”, Journal of Banking and

Finance, v. 27, 5, pp. 1340-1358, TD No. 819 (September 2011).

S. GOMES, P. JACQUINOT, M. MOHR and M. PISANI, Structural reforms and macroeconomic performance

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TD No. 830 (October 2011).

G. BARONE and G. DE BLASIO, Electoral rules and voter turnout, International Review of Law and

Economics, v. 36, 1, pp. 25-35, TD No. 833 (November 2011).

O. BLANCHARD and M. RIGGI, Why are the 2000s so different from the 1970s? A structural interpretation

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Association, v. 11, 5, pp. 1032-1052, TD No. 835 (November 2011).

R. CRISTADORO and D. MARCONI, Household savings in China, in G. Gomel, D. Marconi, I. Musu, B.

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TD No. 838 (November 2011).

A. ANZUINI, M. J. LOMBARDI and P. PAGANO, The impact of monetary policy shocks on commodity prices,

International Journal of Central Banking, v. 9, 3, pp. 119-144, TD No. 851 (February 2012).

R. GAMBACORTA and M. IANNARIO, Measuring job satisfaction with CUB models, Labour, v. 27, 2, pp.

198-224, TD No. 852 (February 2012).

G. ASCARI and T. ROPELE, Disinflation effects in a medium-scale new keynesian model: money supply rule

versus interest rate rule, European Economic Review, v. 61, pp. 77-100, TD No. 867 (April 2012)

E. BERETTA and S. DEL PRETE, Banking consolidation and bank-firm credit relationships: the role of

geographical features and relationship characteristics, Review of Economics and Institutions,

v. 4, 3, pp. 1-46, TD No. 901 (February 2013).

M. ANDINI, G. DE BLASIO, G. DURANTON and W. STRANGE, Marshallian labor market pooling: evidence from

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G. SBRANA and A. SILVESTRINI, Forecasting aggregate demand: analytical comparison of top-down and

bottom-up approaches in a multivariate exponential smoothing framework, International Journal of

Production Economics, v. 146, 1, pp. 185-98, TD No. 929 (September 2013).

A. FILIPPIN, C. V, FIORIO and E. VIVIANO, The effect of tax enforcement on tax morale, European Journal

of Political Economy, v. 32, pp. 320-331, TD No. 937 (October 2013).


2014

G. M. TOMAT, Revisiting poverty and welfare dominance, Economia pubblica, v. 44, 2, 125-149, TD No. 651

(December 2007).

M. TABOGA, The riskiness of corporate bonds, Journal of Money, Credit and Banking, v.46, 4, pp. 693-713,

TD No. 730 (October 2009).

G. MICUCCI and P. ROSSI, Il ruolo delle tecnologie di prestito nella ristrutturazione dei debiti delle imprese in

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TD No. 763 (June 2010).

F. D’AMURI, Gli effetti della legge 133/2008 sulle assenze per malattia nel settore pubblico, Rivista di

politica economica, v. 105, 1, pp. 301-321, TD No. 787 (January 2011).

R. BRONZINI and E. IACHINI, Are incentives for R&D effective? Evidence from a regression discontinuity

approach, American Economic Journal : Economic Policy, v. 6, 4, pp. 100-134, TD No. 791

(February 2011).

P. ANGELINI, S. NERI and F. PANETTA, The interaction between capital requirements and monetary policy,

Journal of Money, Credit and Banking, v. 46, 6, pp. 1073-1112, TD No. 801 (March 2011).

M. BRAGA, M. PACCAGNELLA and M. PELLIZZARI, Evaluating students’ evaluations of professors,

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M. FRANCESE and R. MARZIA, Is there Room for containing healthcare costs? An analysis of regional

spending differentials in Italy, The European Journal of Health Economics, v. 15, 2, pp. 117-132,

TD No. 828 (October 2011).

L. GAMBACORTA and P. E. MISTRULLI, Bank heterogeneity and interest rate setting: what lessons have we

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M. PERICOLI, Real term structure and inflation compensation in the euro area, International Journal of

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V. DI GACINTO, M. GOMELLINI, G. MICUCCI and M. PAGNINI, Mapping local productivity advantages in Italy:

industrial districts, cities or both?, Journal of Economic Geography, v. 14, pp. 365–394, TD No. 850

(January 2012).

A. ACCETTURO, F. MANARESI, S. MOCETTI and E. OLIVIERI, Don't Stand so close to me: the urban impact

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2012).

M. PORQUEDDU and F. VENDITTI, Do food commodity prices have asymmetric effects on euro area

inflation, Studies in Nonlinear Dynamics and Econometrics, v. 18, 4, pp. 419-443, TD No. 878

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S. FEDERICO, Industry dynamics and competition from low-wage countries: evidence on Italy, Oxford

Bulletin of Economics and Statistics, v. 76, 3, pp. 389-410, TD No. 879 (September 2012).

F. D’AMURI and G. PERI, Immigration, jobs and employment protection: evidence from Europe before and

during the Great Recession, Journal of the European Economic Association, v. 12, 2, pp. 432-464,

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M. TABOGA, What is a prime bank? A euribor-OIS spread perspective, International Finance, v. 17, 1, pp.

51-75, TD No. 895 (January 2013).

G. CANNONE and D. FANTINO, Evaluating the efficacy of european regional funds for R&D, Rassegna

italiana di valutazione, v. 58, pp. 165-196, TD No. 902 (February 2013).

L. GAMBACORTA and F. M. SIGNORETTI, Should monetary policy lean against the wind? An analysis based

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M. BARIGOZZI, CONTI A.M. and M. LUCIANI, Do euro area countries respond asymmetrically to the

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U. ALBERTAZZI and M. BOTTERO, Foreign bank lending: evidence from the global financial crisis, Journal

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G. BARONE and S. MOCETTI, Natural disasters, growth and institutions: a tale of two earthquakes, Journal

of Urban Economics, v. 84, pp. 52-66, TD No. 949 (January 2014).

D. PIANESELLI and A. ZAGHINI, The cost of firms’ debt financing and the global financial crisis, Finance

Research Letters, v. 11, 2, pp. 74-83, TD No. 950 (February 2014).

J. LI and G. ZINNA, On bank credit risk: sytemic or bank-specific? Evidence from the US and UK, Journal

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A. ZAGHINI, Bank bonds: size, systemic relevance and the sovereign, International Finance, v. 17, 2, pp. 161-

183, TD No. 966 (July 2014).

G. SBRANA and A. SILVESTRINI, Random switching exponential smoothing and inventory forecasting,

International Journal of Production Economics, v. 156, 1, pp. 283-294, TD No. 971 (October 2014).

M. SILVIA, Does issuing equity help R&D activity? Evidence from unlisted Italian high-tech manufacturing

firms, Economics of Innovation and New Technology, v. 23, 8, pp. 825-854, TD No. 978 (October

2014).

2015

M. BUGAMELLI, S. FABIANI and E. SETTE, The age of the dragon: the effect of imports from China on firmlevel

prices, Journal of Money, Credit and Banking, v. 47, 6, pp. 1091-1118, TD No. 737

(January 2010).

R. BRONZINI, The effects of extensive and intensive margins of FDI on domestic employment:

microeconomic evidence from Italy, B.E. Journal of Economic Analysis & Policy, v. 15, 4, pp.

2079-2109, TD No. 769 (July 2010).

G. BULLIGAN, M. MARCELLINO and F. VENDITTI, Forecasting economic activity with targeted predictors,

International Journal of Forecasting, v. 31, 1, pp. 188-206, TD No. 847 (February 2012).

A. CIARLONE, House price cycles in emerging economies, Studies in Economics and Finance, v. 32, 1,

TD No. 863 (May 2012).

D. FANTINO, A. MORI and D. SCALISE, Collaboration between firms and universities in Italy: the role of a

firm's proximity to top-rated departments, Rivista Italiana degli economisti, v. 1, 2, pp. 219-251,

TD No. 884 (October 2012).

D. DEPALO, R. GIORDANO and E. PAPAPETROU, Public-private wage differentials in euro area countries:

evidence from quantile decomposition analysis, Empirical Economics, v. 49, 3, pp. 985-1115, TD

No. 907 (April 2013).

G. BARONE and G. NARCISO, Organized crime and business subsidies: Where does the money go?, Journal

of Urban Economics, v. 86, pp. 98-110, TD No. 916 (June 2013).

P. ALESSANDRI and B. NELSON, Simple banking: profitability and the yield curve, Journal of Money, Credit

and Banking, v. 47, 1, pp. 143-175, TD No. 945 (January 2014).

M. TANELI and B. OHL, Information acquisition and learning from prices over the business cycle, Journal

of Economic Theory, 158 B, pp. 585–633, TD No. 946 (January 2014).

R. AABERGE and A. BRANDOLINI, Multidimensional poverty and inequality, in A. B. Atkinson and F.

Bourguignon (eds.), Handbook of Income Distribution, Volume 2A, Amsterdam, Elsevier,

TD No. 976 (October 2014).

V. CUCINIELLO and F. M. SIGNORETTI, Large banks,loan rate markup and monetary policy, International

Journal of Central Banking, v. 11, 3, pp. 141-177, TD No. 987 (November 2014).

M. FRATZSCHER, D. RIMEC, L. SARNOB and G. ZINNA, The scapegoat theory of exchange rates: the first

tests, Journal of Monetary Economics, v. 70, 1, pp. 1-21, TD No. 991 (November 2014).

A. NOTARPIETRO and S. SIVIERO, Optimal monetary policy rules and house prices: the role of financial

frictions, Journal of Money, Credit and Banking, v. 47, S1, pp. 383-410, TD No. 993 (November

2014).

R. ANTONIETTI, R. BRONZINI and G. CAINELLI, Inward greenfield FDI and innovation, Economia e Politica

Industriale, v. 42, 1, pp. 93-116, TD No. 1006 (March 2015).

T. CESARONI, Procyclicality of credit rating systems: how to manage it, Journal of Economics and

Business, v. 82. pp. 62-83, TD No. 1034 (October 2015).

M. RIGGI and F. VENDITTI, The time varying effect of oil price shocks on euro-area exports, Journal of

Economic Dynamics and Control, v. 59, pp. 75-94, TD No. 1035 (October 2015).


FORTHCOMING

G. DE BLASIO, D. FANTINO and G. PELLEGRINI, Evaluating the impact of innovation incentives: evidence

from an unexpected shortage of funds, Industrial and Corporate Change, TD No. 792 (February

2011).

A. DI CESARE, A. P. STORK and C. DE VRIES, Risk measures for autocorrelated hedge fund returns, Journal

of Financial Econometrics, TD No. 831 (October 2011).

E. BONACCORSI DI PATTI and E. SETTE, Did the securitization market freeze affect bank lending during the

financial crisis? Evidence from a credit register, Journal of Financial Intermediation, TD No. 848

(February 2012).

M. MARCELLINO, M. PORQUEDDU and F. VENDITTI, Short-Term GDP Forecasting with a mixed frequency

dynamic factor model with stochastic volatility, Journal of Business & Economic Statistics,

TD No. 896 (January 2013).

M. ANDINI and G. DE BLASIO, Local development that money cannot buy: Italy’s Contratti di Programma,

Journal of Economic Geography, TD No. 915 (June 2013).

F BRIPI, The role of regulation on entry: evidence from the Italian provinces, World Bank Economic

Review, TD No. 932 (September 2013).

G. ALBANESE, G. DE BLASIO and P. SESTITO, My parents taught me. evidence on the family transmission of

values, Journal of Population Economics, TD No. 955 (March 2014).

A. L. MANCINI, C. MONFARDINI and S. PASQUA, Is a good example the best sermon? Children’s imitation

of parental reading, Review of Economics of the Household, TD No. 958 (April 2014).

R. BRONZINI and P. PISELLI, The impact of R&D subsidies on firm innovation, Research Policy, TD No.

960 (April 2014).

L. BURLON, Public expenditure distribution, voting, and growth, Journal of Public Economic Theory, TD

No. 961 (April 2014).

L. BURLON and M. VILALTA-BUFI, A new look at technical progress and early retirement, IZA Journal of

Labor Policy, TD No. 963 (June 2014).

A. BRANDOLINI and E. VIVIANO, Behind and beyond the (headcount) employment rate, Journal of the Royal

Statistical Society: Series A, TD No. 965 (July 2015).

G. ZINNA, Price pressures on UK real rates: an empirical investigation, Review of Finance, TD No. 968

(July 2014).

A. CALZA and A. ZAGHINI, Shoe-leather costs in the euro area and the foreign demand for euro banknotes,

International Journal of Central Banking, TD No. 1039 (December 2015).

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